How I created a web and mobile application within an hour without coding Amazon introduced the beta version of its no-code application development platform Honeycode a week ago. No-code, Low-code software development platforms aren’t anything new, they have existed in the industry for the last two decades; however, despite their presence, most of the software applications are still developed through hand-coding performed by programmers. Creating an application that can be used by businesses themselves is a wish that every enterprise is likely to have considering the time and cost incurred in the traditional development of software applications by programmers. Honeycode Account, Workbooks & App Templates When you create an account in Honeycode, you are an ‘Admin’ for your workbooks and apps in Honeycode. You can invite your team members to use the apps that you created. While team members can also be made admins of your workbooks and apps too, they will simply be a ‘member’ for your apps. Honeycode works similarly to if you were to create an application directly from a spreadsheet. Honeycode users can import a ‘csv’ file into Honeycode to create a ‘Workbook’, which is a collection of apps. A few predefined app templates are available on the website, which can be readily used or modified to suit your needs. I wanted to create an application from scratch. My intention was to create a tiny app through which a user can submit Travel expenses for the business trips. Key Components The following are the key components for creating apps in Honeycode. — Similar to any spreadsheet or database tables Tables — Using this you can build the screens for the app App Builder — For creating navigation, workflows, and notifications Automation Step 1. Create Tables Creating Tables through the GUI as simple as you do in any other tool. Table columns can have standard data types. A new data type ‘Contact’ is available where you can map the Admins and Team members of your app. Step 2. Create App & Screens After the tables are created, you can choose to create the app using a Wizard feature available in App Builder. You should choose the tables for the wizard to create the screens for that. For each table, the following screens are created by the wizard — 1) List screen 2) Details screen 3) Data Entry Form. I chose to create the screens from scratch. Screens can be built with objects from the palette. For user-interactive objects, the data can be taken from the tables using formula. If static text objects like ‘Content box’ (labels) too, a data cell can be associated if they should display dynamic text. Step 3. Add Automation Actions Button-like objects can be associated with actions through automation. In the Submit button of the screens, I have added automation to insert the entered values to the table and then to navigate to the next screen. Actions can be also be added to notify the users (contacts) through email, overwrite the form’s field values, and to update the records in the tables. Web & Mobile Views The image below is the Submit Expenses screen from the web application. For previewing the mobile view, you need to download Honeycode mobile app on your mobile. The following image is from the Honeycode mobile app for Android. Conclusion I was able to create the app, both for web and mobile, within an hour. As I became better acquainted with the tool, making progress became a far less time-consuming experience. Honeycode community has got help docs in many topics, which can be referred till we get more content after the active adaption of the technology. Looking at the questions in the community forums and the responses from the Amazon team, I understand that Honeycode has been released as a B2E (Business to Employee) platform for the creation of ‘internal’ applications. Enterprises who are planning to automate their business functions may find Honeycode useful. If the platform is enabled to be used for creating applications for customers and the public, I’m sure that many would find it a very attractive alternative to existing technologies. Previously published at https://codeburst.io/a-no-coding-experience-with-amazon-honeycode-1a824f0c5567

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Amazon Honeycode: A No-Code Platform With Big Promise

Tailwindcss provides a modern spin on writing css. And unlike bootstrap, it allows us write css without predefined classes i.e we can create our own custom styles without external opinions on how things should look. Setting up tailwind is pretty straightforward, but with React, it might seem a little daunting. Here’s a quick tutorial to get you started creating awesome class-based inline styles using tailwindcss. 1. Create a new react app(duhh!). & & npx create-react-app tailwind-app amp; amp; cd tailwind-app 2. I like to write my css in SASS so let’s setup SCSS. Run the following command to install the SASS package. npm install node -sass 3. Install all the packages we need; tailwindcss itself, postcss-cli(helps us extract tailwind utility classes into our own css files) and autoprefixer(helps us ensure that the CSS we write is supported in all browsers). Let’s install them as development dependencies by using the flag. -D npm i tailwindcss postcss- autoprefixer - cli D 4. Run the following command to generate a tailwind configuration file. This file contains all the tailwind classes. npx tailwind init --full you should now see a file in your app directory. tailwind.config.js 5. Now, we need to setup our Postcss config to help us build our css files. First, let’s create the configuration file. touch postcss .config .js 6. Next, copy and paste the following code into the file. This block of code tells postcss to use the and plugins when creating out css/scss file. postcss.config.js tailwindcss autoprefixer Autoprefixer is a CSS post processor. It combs through compiled CSS files to add or remove vendor prefixes like -webkit and -moz after checking the code against caniuse.com. .exports = { : [ ( ), ( )]
}; module plugins require "tailwindcss" require "autoprefixer" 7. Next, let’s create a directory. I like to keep my folder inside my folder Inside the src/styles directory, create a file and also move your file in here. Rename your to styles styles src . tailwind.scss index.css index. css index. scss Make sure to update the reference to in your to index.css index.js “./styles/index.scss” 8. Head into the tailwind.scss. We need to inject the tailwind utility classes into the file. Add the following code. We specify the tailwind utility classes we want in the tailwind.scss file. From here, will extract the classes from the declarations and pushes them into our file as you will see. postcss index.css @tailwind base;
@tailwind components
@tailwind utilities 9. Finally, head into your file. We need to make some changes to our scripts here to ensure that bundles all our css from into our file First, we create a script. We use the command (made available by the postss-cli) to extract the tailwind classes from tailwind.scss and output it into index.scss package.json Postcss tailwind.scss index.scss . build:css postcss " ": {
   "start": "npm run :css && react-scripts start build npm run build:css && react-scripts build test react-scripts test eject react-scripts eject build:css postcss src/styles/tailwind.scss -o src/styles/index.scss scripts build ",
   " ": " ",
  " ": " ",
   " ": " ",
  " ": " "
} Your package.json scripts should now look like above. Simply run like you normally would and your app should start running. You would notice that our file now contains all the css classes tailwind provides. npm start , index.scss All the tailwind classes are now available to use. I like to refer to the documentation to see the class names sometimes but generally, a lot of the class names are intuitive if you’re coming from bootstrap. If you’re looking to add additional CSS styles, you can add them inside the tailwind.scss file we have created. Each time you make a change to the file, you would need to rebuild the css by stopping the server and running again NB tailwind.scss npm start . Previously published at https://medium.com/@adebola.niran/how-to-setup-tailwindcss-with-create-react-app-and-s-b7243607c3e7

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More and more developers are currently deciding to boost their workflow, minimize unnecessary tasks, and structure their virtual desks through admin panels with Node.js backend. Why Node.js you may ask? Node.js is a JavaScript runtime environment. That means that the main advantage of using this platform is that you can have frontend and backend in one programming language. That allows you to synchronize the data in both parts of your app. That speeds up the development process significantly. Admin template with Node.js backend not only provide you with ready frontend part of your application but also include some pre-made backend. Various login methods, product management, CRUD application, PostgreSQL can be already integrated with the admin panel. There’s no secret that becoming bigger, better and stronger within your development role requires some form of a switch or shift, in order to allow you to work productively. There’s a big difference in being productive and being busy, although the main key to effectively engage in this type of switch, is to equip yourself with the accurate tools. Today, we’ll do just that. We’re going to bounce through five various admin templates with Node.js backend, in order for you to improve your developing-productivity today. Light Blue React Node.js Admin Template Light Blue React Node.js is a React admin template integrated with Node.js backend and PostgreSQL. It’s an extremely good fit for anyone looking to build E-Commerce apps, CMS, SASS web apps, CRM, etc. since it contains ready-to-use working Authentication, Social Login and Product Management components. The template also comes with 60+ ready-to-use and customizable UI components. In order to get started, all you need to do is to deploy the app and you’re good to go. Features PostgreSQL integrated CRUD Application 60+ ready-to-use and customizable UI components React 16.5.2 Deep Background 8 Chart Libraries E-Commerce section Learn more Demo Documentation Argon Admin Dashboard Pro Node.js For this admin template, Creative Tim partnered with Udevoffice to provide a fully coded “frontend + backend” solution. It features a great number of components in order to help you create any website you desire. The main benefit of this dashboard is it provides a lightweight, fast, scalable and modern way to build your app. Features 16 customized plugins 200 handcrafted elements 25 example pages SASS Files Sketch Files Learn more Demo Documentation Sing App Vue Node.js Admin Template Sing App Vue Node.js is an admin template integrated with Node.js backend and Postgres database. Product management pages and various login methods already implemented and ready to use. The app is ready to be deployed to any amazon aws, heroku, etc. It will be a great starting point if you are building SAAS, CMS, E-commerce applications and want to save time and money. You’ll also be greeted with 60+ ready-to-use and customizable UI components. Features 60+ ready-to-use and customizable UI components The latest version of Vue.js CRUD Application PostgreSQL integrated Theme SupportE-Commerce Section Static & Hover Sidebar Learn more Demo Documentation Node.js MongoDB Starter Bundle This bundle is the a minimal package of ngx-admin integrated with Node.js backend. It contains JWT Authentication for both UI and Backend and Basic User Management. You’re able to choose from two different bundles based on your needs: the Starter Pack or the E-Commerce Kit. E-Commerce Kit has some additional features such as order details page and sample order table. The dashboard is based on Angular ngx-admin, Express REST API, MongoDB, and other popular and useful technologies.  If are searching for documentation for this template, you should know that documentation is supplied with deliverable archive. Features Angular and Node.js Projects ExpressJS, MongoDB Intergration Public and JWT secured API endpoints Auth/Register/Password recovery forms and APIsProfile page CRUDL Learn more Demo Lexa Admin Template Lexa is built with Bootstrap 4, Node.js and JQuery. It’s a fully responsive and have the clean user interface that includes a great collection of components, widgets, and UI elements. Horizontal layout of this admin template is looking good, this is a very nice peculiarity. Lexa have maintained a very high quality code for all versions so developers can easily customize it according to their requirements. It is a flexible admin template and can be used to build all kinds of projects. Features Horizontal & Vertical Layouts Node version 9.11.2 SASS SupportLogin, register, error pages Calendar view Form validation Invoice with ready print button Directory List page Google maps Drop zone file upload Summernote Editor6+ Charts Library Datatables Learn more Demo Text source: - React, Angular, Vue, Bootstrap & React Native templates and themes. https://flatlogic.com The link to the original article: Top 5 Admin Templates With Node.js Backend

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Top 5 Boilerplate Admin Templates With Node.js Backend

The scariest thing you never want to hear come from an automated recording from your primary care physician’s office are the words “we are closed indefinitely until things clear up”. Where are you supposed to go? Who are you supposed to call? And there’s no way you’re going to the nearest hospital to rack up a $3,000 bill just for stepping foot through its emergency room doors. That’s why you want to make sure your physician has the appropriate technology so that you never truly are out of reach for medical care. But with medical imaging technology continuing to evolve rapidly in today’s digital age, why is it, for decades, we haven’t seen the equivalent speed in the methods by which images are displayed? And why is it when this “rapid” change came about, it was the direct result of a global pandemic that out of nowhere six months ago, has claimed the lives of over 116,000 people in the United States, with over 2 million confirmed cases? The global outbreak of the coronavirus has not only affected our reality as we know it, but also our augmented reality. Valued at $850 million, the augmented reality market is already changing the ways in which clinicians see data and their patients. Expected to reach $5.1 billion globally by 2025 (or even sooner thanks to COVID-19), the augmented reality industry has already begun disrupting the healthcare industry. Augmented reality (AR) allows for digital information to be superimposed and integrated into our physical environment (augmented). From technologies like Google Glass and Microsoft Hololens to Zenerchi’s open-source physiology simulation visualization, the healthcare industry certainly has shifted from our physical reality to augmented reality. We all hope we live to see the day where we hear the words “we’ve discovered the cure for cancer”. Unfortunately, that day will never come unless we are all willing to accept the truth—it will take something much bigger than us to help us reach that destination. It is for this reason, that depth perception becomes an invaluable component to medical examination when we are talking about AR. The ability to observe and explore vital organs and blood vessels in our current technological capacity can no longer be done with accuracy. Only with AR technology can this help keep our healthcare industry flourishing and intelligent. COVID-19 has exploited hundreds of thousands of weaknesses and vulnerabilities in our global infrastructure, while simultaneously revealing one necessary truth: it’s time to adopt the technology before us or be swallowed up whole—literally. And companies aren’t taking chances anymore. We’ve seen company after company goes under—even some we never thought would, and why? Because of an inability to accept the truth. That in order to survive in today’s digital age, you must inject digital infrastructure into an already existing physical infrastructure. It’s the only way. We saw this immediately following the COVID-19 outbreak when Utah-based biotech company Zenerchi published its looked like (before any company out there was able to wrap its minds on what was going on). AR-simulated educational video that augmented what COVID-19 Utilizing the Zenerchi platform, the company was able to produce both the content and video in a matter of days that included , using its custom COVID protein viewer for the world to see and comprehend, so that COVID is more than just a word. detailed micro-and molecular biology Back in May, National Bioskills Laboratories, a leading provider of surgical training facilities, unveiled its medical-grade remote physician training platform in response to the travel restrictions COVID-19 placed upon surgeons who traveled for educational purposes or patient consultations. The platform, ™, combines high-resolution video live streaming from medical devices with real-time, collaborative audio-conferencing capabilities specifically designed for physician skills-training. National Bioskills Live Connect The solution is capable of streaming multiple video outputs from surgical cameras and medical equipment (such as C-arms or ultrasound machines) simultaneously. “We can’t accept lag times, fuzzy images, or unsecured technology,” Douglas Hampers, the company’s CEO says. “So we designed a medical-grade system to be 100% reliable with razor-sharp images and real-time audio, and top-tier security that is HIPAA compliant.” But Dr. Hampers and National Bioskills Laboratories aren’t alone in this battle, as the company adds serial entrepreneur and visionary Jon Fisher and CrowdOptic to the mix. The company uses cloud-based software and proprietary hardware with Intel components from Fisher’s company, which is an augmented reality firm using algorithms and real-time sensor data from electronic devices to enhance security, social media sharing, and advertising. Fisher, a known visionary behind Bharosa, a leading provider of fraud prevention and authentication-security solutions that was for a reported $50 million in 2007, continues to grow his digitally adaptive entrepreneurial portfolio by the year. acquired by Oracle His company’s technology has been implemented in everything from sports to medicine to government. It was also the first patented solution for wearable technologies, such as Google Glass. As for NBL, the company was founded by board-certified physicians and educators with the desire to improve patient outcomes by using CrowdOptic’s state-of-the-art facilities to help train doctors on proper techniques when working with new medical implants. “With its partnership with CrowdOptic, NBL can now reach a nearly unlimited number of physicians, healthcare workers, and sales teams,” Fisher shared with us. “NBL now has the ability, thanks to Live Connect™, to take this technology and empower anyone to create their own teaching environment anywhere in the world. Now ORs, surgical centers, and home offices can set up their own teaching studio for an unlimited number of people to learn and interact remotely. The more people that can improve their education, the better the outcomes for all patients will be.” And here we are today, thirty years later after telemedicine came about, where cloud computing, deep-level analytics, and artificial intelligence (A.I.) control how “accurate” our information technology systems generate information. Yet, despite our technological advancements, the outbreak of COVID-19 taught our world a very valuable lesson--we weren’t technologically ready to go “digital”, despite our ability to do so. With federal regulations and stay-at-home orders in place, COVID-19, according to Dr. Hampers, made holding large-scale teaching events essentially impossible. “Doctors will now have to train in much smaller groups and the number of doctors that can be trained will be very limited. Virtual training will allow for more accessibility to this type of training for all those physicians that could not attend, nor didn’t want to take the risk of contracting the virus by having to travel to a laboratory-type event.” But more importantly, the ability to watch experienced surgeons in the OR in realtime helps an enormous number of doctors who have never performed a certain type of surgery or perhaps need to “brush up” on the proper techniques for that particular surgery. And Fisher is extremely optimistic about the direction physician care is heading: “With the rapid adoption of this technology, we believe the next five years will see enormous advancements in video analytics as it relates to the medical industry. CrowdOptic and NBL will help lead that change.” With Fisher and CrowdOptic involved, the National Bioskills Laboratories system compresses video files and transmits them securely via enterprise technology protocols for optimized speed, reliability, and scalability, with additional security provided by . OneSpan's Intelligent Adaptive Authentication In this portable “plug-and-play” system, all the necessary hardware components are shipped in a small, protective case to anywhere in the world, and can be set up at the host location in less than 20 minutes by non-technical staff. Host users need only a power supply and an internet connection to live stream to remote attendees who log in to a secure web page. Previously, the challenge of educating the industry on adopting remote-training solutions has been overcome, thanks to the lingering effects of COVID-19. “In the past, we needed to get the industry to understand that the medical product companies would experience better adoption of the devices and much better outcomes for patients, due to the better overall training of the physician,” Fisher added. “COVID-19 has essentially eliminated these obstacles.” Put aside the video games folks, because if you truly want to see the success that AR can bring to our world, it starts with our fundamental health. An apple a day may keep the doctor away, but in a time where COVID-19 effectively shut down our world for over six months, AR technology is the only thing saving our day.

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An Apple a Day Keeps the Doctor Away— But With Global Pandemics At Play, Augmented Reality Must Stay

With this browser extension, . you can mark and save the words you don’t understand while using your favorite online sites is a brand-new system designed to help anyone accessing the to improve their vocabulary in a snap. Burning vocabulary web Mark words on BBC News If you regularly use and you would like ongoing corrections for your posts, the browser station can work in the background as you are typing your latest post or reading through content online. If you ever need a quick explanation on a word or you would like to receive a bit of vocabulary help as you are typing, the application can provide you with an ongoing guide in a pop-up menu. social media As you are typing or reading a sentence, you can simply right-click any sentence in your browser to get a drop-down menu on the definition, translation, and some other synonyms that you could be using. This tool can help you to expand your English vocabulary, improve your ability to communicate, improve your ability to understand content online, and more. Vocabulary Calendar Burning vocabulary makes the process of your favorite vocabulary on Twitter or Facebook, a very natural process. The tool can be extremely useful for anyone that regularly communicates online for business or for anyone that is interested in improving their English vocabulary for free. learning Official website screenshot Free online instantly friendly dictionary, an extended premium version is also available. Here is the . Chrome web store package

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1+1>2 Since 2017, thriving innovation in cryptocurrencies and blockchain has formed a strong force that the world can no longer ignore. I believe in the coming years, the boundaries between “traditional” consumer fintech companies and cryptocurrency will become even blurrier, as the former can leverage crypto-assets to create new revenue streams. With more leading consumer fintech companies and startups expanding services related to crypto-assets or even issuing their utility tokens, the ones that don’t may take the risks of losing a great pie of potential market shares. For crypto-native projects, their participation can create a tipping point for mass adoption. Positioning cryptocurrency in the consumer fintech space Let’s give cryptocurrency a new perspective on the industry-level. Consumer fintech companies are the ones that offer financial services that cater to consumers’ needs, including consumption, investment, borrowing, savings, and transfer that each can be satisfied by a certain type of company. In the next few articles, I’ll dig into the application of cryptocurrencies in each company type. (selected companies are mostly in the US/EU/UK) Enter crypto in the consumer fintech space Why now? The industry backdrop of consumer fintech Taking a closer look at the recent trend of consumer fintech space, the following points are the ones I think will further incentivize companies to adopt cryptocurrencies. Cashless payment COVID-19 has accelerated the of cashless payment, especially in regions that previously have lower penetration of digital payment. With more transactions moving from cash to mobile phones, companies will have broader target customers of potential crypto services in finance, which are usually taken place on mobile phones. trend Rise of peer-to-peer (P2P) transfer Recent financial results of leading fintech companies like PayPal, Square, and Western Union show that P2P transfer has shown strong growth. However, the er transfer itself usually doesn’t charge any commission. Offering services related to cryptocurrencies provides an additional way to monetize these users. Monetization of these customers effectively has become a core strategy for these companies. Paypal and Zelle have shown strong growth in P2P payment Serve the unbanked/underbanked In recent years, startups began capturing the trillion market opportunity of the and the , who are usually unqualified for certain or all banking services. unbanked underbanked The application of cryptocurrencies, with relatively lower transaction fees on the blockchain, can empower startups to serve cheaper financial products than the incumbents. , a remittance startup targeting overseas workers from the Philippines, converts remittances into cryptocurrencies before being sent to the receivers as fiat. Coins.ph Also, for the startups that have already targeted the unbanked/underbanked population, offering crypto-related services can differentiate the product and expand the customer base. Revolut, the leading challenger bank based in the UK, has its crypto trading services last month. expanded Why will more companies integrate crypto in consumer fintech? In short, cryptocurrency can be the next driver of their revenue. When new technologies are ready to be implemented, new business models emerge. Just as the with AI and big data, cases consumer fintech companies have integrated cryptocurrencies into their business models. For leading companies, currently, the customer-facing (2C) business models related to cryptocurrencies mainly include (ex. Cash App’s buy & sell service of Bitcoin), integrating crypto-assets (ex. Visa’s recent of crypto debit card in EU and UK), and s (ex. offers crypto custody for both institutional and individual customers). trading or direct selling of cryptocurrencies the extension of existing services approval new services for crypto-asset Fidelity In addition to these models, existing fintech startups that are smaller in scale than the incumbents have more flexibility of as a way to enhance users’ engagement (ex. gives you rebate in its tokens after certain consumption with their service). issuing their utility tokens Wirex In the past year, with the popularity of Bitcoin rising, some fintech startups have been planning to integrate both fiat and cryptocurrencies from the start (ex. Plutus allows you to buy brands, including Nike, with up to 3% rebates in its tokens). As for crypto-native startups, with technological improvement of blockchain and token economics, unconventional business models can emerge such as what we have seen in Decentralized Finance (Defi) projects. The business model of cryptocurrencies In my view, with these business models integrating cryptocurrency, companies can achieve revenue growth from these dimensions, including , , , and . product differentiation/diversification acquisition of new customer cohorts increased customer engagement monetization of existing customers Moreover, with crypto, consumer fintech companies can expand to other types of services effectively like payment to trading. How crypto can bring revenue growth The revenue growth effect has already played out. In the latest quarterly financial result, Square’s Cash App 306 million dollars from Bitcoin trading, accounting 22% of Cash App’s total revenue, up from 6% in the previous quarter. PayPal’s Venmo, Cash App’s competitor, is also recently to begin Bitcoin trading services. reported reported Implications for crypto-native projects With a larger customer base and lower barrier to entry for mass adoption, I believe the trend of consumer fintech companies integrating cryptocurrencies is extremely positive — for the ones determined to create value. While the crypto community will face more competition from the existing fintech companies, the trend can create higher standards of talents and user experience for crypto-native startups to stand out. The trend can also attract more capital to the crypto world. Early-stage crypto-native startups will also more likely to become potential targets of acquisition by leading fintech companies. For the ones that are already sitting on piles of cash, mostly crypto exchanges, direct investment/ M&A activities will also become even more active than now ( ). Coinbase, Binance, and Kraken lead in blockchain M&A deals While the business models with crypto mostly still revolve around Bitcoin now, I expect , given stable coins’ advantages compared with fiats such as almost-instantaneous transfer, lower commission fees, and 7/24 settlement. regulated stable coins will be integrated into more consumer fintech companies and leading financial institutions in the future But one thing is for sure — more innovation will come up when the world between fiat and crypto gradually merge into one. After all, innovation knows no boundaries.

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Consumer Fintech & Crypto currencies: The Twain Shall Meet

Hello, Dear reader! 🧑‍💻 Here I talk about the Constellation Network, Inc. Why I think the Constellation is one of the most amazing companies! Why they will steal the show and create and set the standard for future Cybersecurity for Big Data. I give arguments to which I paid more attention than to others, as possible clearly and briefly. Go! We are well underway in the Fourth Industrial Revolution.  This industrial revolution, unlike previous industrial revolutions, is characterized by as the “fusing of the physical, digital and biological worlds, impacting all disciplines, economies and industries, and even challenging ideas about what it means to be human.” (Klaus Schwab). As You know. Of all the recently developed technologies, it is probably the blockchain and its capabilities that are changing the world more noticeable than deserve attention, research and participation. There are several areas that, like a number of technology projects, can benefit most from the capabilities of the blockchain. The last 10 years have been marked by the emergence and immense growth of the Big Data industry. Whereas the first implementation of blockchain technology was the Bitcoin network, which appeared in 2009, the technology is now being widely integrated into other industries to maintain the reliability of their data. The use of blocking technology will transform profiling industries. Blockchain Overview Blockchain is the underlying technology powering many cryptocurrencies and has thus found itself into isolated use cases around financial services and instruments and supply chain management. Existing blockchains have had limited use cases beyond the aforementioned because of scalability and compatibility limitations in the technology. If entrepreneurs, investors, and engineers can pave a path through overcoming of these primary obstacles, then we will see wider support of the technology. Nowadays, blockchain is becoming a synonym for distributed ledger technology. However, blockchain is only one of the specializations in the field and is currently well-covered in of a cryptographic space. Besides blockchain technology, a new paradigm is gaining momentum: directed acyclic graph (DAG or dag). - a digital currency powered by synchronous blockchain technology. Characteristics: decentralized, Proof of Work consensus. Main area of application is focused on the asset and store of value aspects. Limitations include slow, not scalable, and no application support. Generation 1: Bitcoin - the development of the Smart Contract paved the way to more use cases beyond financial instruments and incorporated simple homogeneous data sets. It sparked the discussion around blockchain being used as an immutable audit trail around a ledger and wallet balance of an asset. Characteristics: application support, Proof of Stake consensus (ETH 2.0), assets, simple data sets in Smart Contracts Limitations include: slow, not scalable, not compatible with existing infrastructure and data management, and limited application support. Generation 2: Ethereum - a micro-service and state channel supported ecosystem for big data use cases. A new standard to create an immutable audit trail while cryptographically securing heterogeneous and complex data structures. Characteristics: Application support for developers, directed acyclic graph (DAG - graph based database), Proof of Reputable Observation (PRO) - a reputation bases consensus, a horizontally scalable infrastructure with dynamic partitioning, and compatibility with existing data management solutions. Generation 3: Constellation Network So, Blockchains, a specialization of DLTs, are getting a new rival in the field: distributed acyclic graphs (DAG). The most notable difference between the two is that blockchains bundle transactions in cryptographically linked blocks forming a single chain containing the global truth, while DAGs use a graph where a transaction is represented as a node in the graph. I don’t have time to go into that but it is quite interesting, trust me. There are other DAG systems out there that you may have heard of, like IOTA, Nano, Fantom и Hedera. It’s a competition rich niche already. Over the past couple of years, we have seen an evolution of blockchain technology #dlt. Blockchain has the potential to make exponential improvements to the way organizations operate and communicate, especially with regards to how we share data. How can Blockchain Help? The world creates extra large massive of data everyday and exponentially more devices coming online to exponentially more data. We have created a world where we have to redefine data strategies to accommodate threat vectors such as spoofing of devices, rich databases, and existing IT investments and infrastructures. Every business relies on intelligent data to run the organization and create competitive advantages against other companies or countries. Companies require databases to support rapid spikes in data volume, be horizontally scalable, provide high throughput without downtime, custom code, and delay. I believe that we will see multiple government and enterprise will to migrate aspects of their business over and onto blockchain technology to minimize inefficiencies and improve margins. Nearly every government and enterprise is addressing how blockchain can be incorporated into their existing systems and used to create improved operational processes. Specifically, there has been an emerging interest in blockchain being applied to use cases that address threat vectors around data privacy issues, interoperability between machines, and data security. Traditional blockchain use cases lend themselves to cryptographically securing financial transactions and ledger balances [of financial instruments, supply chain tracking and data], but not actually cryptographically securing complex data structures and schemas. Which would broaden the use cases to included data science and big data applications such as data validation and integrity analytics and machine learning. Constellation believes that a blockchain-like solution, directed acyclic graph and protocol, is the perfect solution for an organization looking to minimize centralized network security threats and where data is critical for missions and operations. Constellation is positioned as the Blockchain for the Big Data market. While enterprise and government entities are exploring blockchain, success of the industry will rely on the crypto/blockchain companies themselves developing applications and use cases. The real winners in the space will be those that attempt to that zero in on one or a couple of the obstacles that exist. My general point is that Constellation are very mindful of the hurdles that exist for the blockchain and cryptocurrency space to come into maturity. Constellation (DAG): Cybersecurity for Big Data Applications driving big data like the AI industry and IOT Industry are putting new constraints on the security of digital infrastructure. Constellation allows you to implement security and auditability for complex datasets without changing existing IT infrastructure. It’s secure, cost-effective, scalable, and easy to integrate. Constellation is the first scalable enterprise-grade blockchain creating a standard for securing data in transit (between digital systems and hardware) and use (applications like artificial intelligence, business intelligence, analytics, and IoT) by cryptographically securing complex data structures. Constellation’s technology aims to facilitate secure big data processing by offering the ability to on board external data sets through easy to use API’s that integrate directly in existing applications.  By utilizing a DAG (directed acyclic graph) protocol and customizable state channels, Constellation embraces an evolution to smart contracts that enables new data sources to integrate on DLT. Let’s dive in Tech. Constellation’s Directed Acyclic Graph (DAG) and consensus model, called Proof of Reputable Observations (PRO),  allows to organize the network to match throughput needs of enterprise databases while handling higher-level consensus to prevent double-spends and malicious behavior. Furthermore, consensus enables to identify malicious behavior and nullified nodes while then applying topology to optimize the network for security and high throughput computational needs for databases that require speed, agility, scale for their varied use cases. Constellation provides cybersecurity developer tools that are integrated early in the development workflow and leverage the resilience of a blockchain network and encryption with compatible architecture and scalability of big data management solutions (like MongoDB, Kafka, Splunk). Key characteristics Constellation Network (DAG) Below is a highlight of how Constellation approaches some general technological features often encountered in the blockchain space. Moving away from centralized systems mitigates the network away from as single point of vulnerability. Additionally, Constellation will allow organization to choose between off-chain and on-chain data management. Improved Security. DAG technology offers new ways of processing transactions, that are currently not possible in traditional systems. Hypergraph is different to all other DAGs in that it scales horizontally, it scales infinitely, and is designed to handle all of the world’s data. There is absolutely no limit! Infinitely Scalability. Constellation focuses on JVM and Scala as the main programming languages, with more that 9 million developers world-wide, to simplify the development of new applications. Their aim is to equip engineers with new scalable infrastructure technologies to provide cybersecurity for big data. Ease of Adoption. Tokenized throughput on the Constellation network, that allows the value of data to be bound to a token. While basic transactions will remain free, big data processing & exchange will require DAG as payment. Reward for Node Operators. Tokenomics. Technically speaking $DAG is the financial state channel of the Constellation Network. It allows the seamless exchange and interaction between the various state channels and nodes that make up the network. $DAG binds the components of the network together and enables them to relate to each other. With the launch of Hypergraph Network the next stage of Constellation and DAG begins. After nearly 2.5 years in development the Constellation have officially launched main network, called Hypergraph, and ERC-20 Token has been swapped for native $DAG currency.  Their original roadmap said Q1 2020, and even with COVID, they hit it on the mark.  The network successfully launched on time with approximately 15 node operators that are already earning validator rewards and the Constellation team expect to onboard 80+ more validators in the next few months. runs on fully decentralized nodes spread around the globe. The PRO consensus is reputation based and unlike anything else out there. It saves energy in comparison to POW and is more fair than POS.  Full horizontal scalability ensures unlimited TPS growth with more nodes on the network. The DAG Hypergraph This transition should mark a big change for both Constellation as a company and DAG as a token. The team is already actively working with multiple agencies in the US Federal Government to use Constellation’s technology to validate and secure big data to evolve digital infrastructure in the United States and beyond. I think not only me feels it’s so cool about a blockchain company working with federal agencies! I'm glad to be a part of this incredible journey. And I'm is sure that their new technology will be a game changer and open new doors and opportunities in their fields of big data and cybersecurity. Concluding Thoughts Constellation (DAG) has been in the cryptocurrency space for a while now. They seem to have the long term thinking trait that not many other businesses possess. Their target business is focussed on cybersecurity and Big Data. And their actions show they are thinking far beyond the average crypto! For me, one of the most convincing aspects about Constellation is their approach to business development. For starters, Constellation is heavily product focused. They are attempting to disrupt a huge industry by creating a solution that is significantly better than existing alternatives. There is a drive to create distributed ledger technology (DLT) innovations because they view it as a necessary component for the growth of their business in the long term. Besides building a competitor-beating product, Constellation is focused on building real partnerships that should pay dividends over time, - which will ultimately lead to adoption if they manage to build a reliable platform. Be sure to watch the video, think about it, and make your move 📍 Ben Jorgensen - CEO and Co-Founder of Constellation Network, Inc. - provides a detailed update on Constellation, the vision for the next three years, the role of $DAG currency in the ecosystem and roadmap, and the path to adoption (technology, community, business). Coffee talk with Wyatt Meldman-Floch Co-Founder and CTO and the team around where Constellation is going and why DAG is a revolutionary and novel technology. Role of DAG, value of data, tokens, datatypes & data structures. Read their . Vision Paper This sounds very impressive and brings me to the next general opinion about Constellation. Summary The current crypto landscape has become increasingly saturated and competition is rife, it is more difficult now than ever before to pick the winners in the space. is a very interesting and profitable project (in the long run), the team of which has set itself a gigantic task: create ! Constellation (DAG) a new standard for secure data transportation To me Constellation is the synthesis of strong technology, business acumen and community awareness into project narrative. Constellation is a response and acknowledgment of the power that is inherent in information and data. Constellation embraces our future and has built a technology crucial for what lies ahead. Secure and validated data is the key to unlocking a true data exchange. Thanks for reading! 👋 If you like this article dont forget to share it! I will be grateful if you support my work by your LIKEs and comment. 👥 Disclaimer! This article does not provide investment advice nor is it an official representation of the project mentioned. It’s an opinion piece. It is for educational purposes only! I hope it will be relevant both to folks who are new to the space, as well as those who already know about Constellation ($DAG).

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During the last decade, social networking sites/apps have become the most important channels of communication. Social networks such as Facebook, Twitter, and Instagram contain a considerable amount of informative data not only about social matters but also about business and marketing. Of course, if you want to take advantage of this ever-changing space to swing the balance in your brand’s favor, you don’t have a choice unless using big data analytics. In this post, I’m going to describe how social media can be affected by and how businesses can make the most out of it. big data analytics What is big data? Big data is any novel technique used to analyze a massive volume of data that is so large it is impossible to process with traditional methods. Big data can handle both structured and unstructured data and help you tackle the problem of processing power. The main purpose of using big data techniques is finding overall patterns, trends, and connections between different variables. This is particularly important for studying data related to human interactions and social behaviors. This is exactly where social media can be influenced by big data, especially for marketing purposes. In fact, the huge, unstructured knowledge available on social media can’t add real value to your marketing strategy. So you need a powerful tool like big data analytics to be able to handle it. Important data on social media The stream of social posts, likes, mentions, shares, followers, and many other impressions can clearly prove why big data is important in social media marketing. This is now a must for businesses to collect these tones of information in real-time and analyze it to know how well their social presence is. In fact, every single positive interaction can add to their reputation and any negative feedback can put their efforts at stake. Without the shadow of a doubt, , especially for big companies, can’t be impactful without big data. Therefore, many businesses are investing masses of money on big data tools to track real-time consumer behavior across social media. social media marketing analytics To do this you will have to: Collect the most related data available on social networks Recognize the weight of each data on your target market Convert these data into useful facts and use them in your strategies Of course, the velocity of your data mining, the volume of the data, and also its variety is of paramount. You’ll need to use the best data technology and analytical tools if you want to leverage big data in marketing effectively. Also, it’s important to consider integrating various social networking sites/apps. Using Facebook, Instagram, Twitter, and LinkedIn will lead to better social interactions and the data from them can represent reality more exactly. Advantages of big data for digital marketing A lot of big and small companies are thinking about considerable budgets for big data analytics tools to get ahead of the competition. Here are 5 top benefits a big data analysis approach can bring to your social media campaign: 1. Taking care of huge information sources As a social user, you may need to process all data related to your niche that comes from mainstream channels. Analyzing diverse channels is not an easy task and can only be done by using artificial intelligence and big data technology. A lot of business sites allow users to sign up via Google or other main channels. So marketers can collect and analyze data about their niche customers from social networks, browser history, applications, cloud storage, etc. 2. Targeting the right audience It’s clear that you can’t reach out to all the internet users so you have to narrow down to the most probable group of customers. Thus, social media marketing is all about identifying your target audience. Big data technology has provided marketers with access to insightful data of users’ personal information, photos, favorites, locations, and various kinds of activities. 3. Predicting online behaviors A big data approach can also be used for better decision-making based on previous trends. Data-based businesses are becoming incredibly efficient, as computers can predict the potential choices of customers. In sum, the interests and habits of people can be estimated as they’re changing based on specific overall trends. 4. Managing marketing campaigns Big data techniques enable marketers to accurately track the ROI metrics of their social media campaigns. It will provide advertisers with insightful data into how effective a social media campaign has been or can be. Predictive analytical methods greatly help in predicting what products/services consumers want. Tracking consumer behaviors all over social will clear many things about the effectiveness of previous campaigns. This includes media including their engagement and reaction to online advertising. So marketers can optimize their plans for future campaigns to get a higher ROI. 5. Identifying fair prices One of the biggest problems for marketers is to find reasonable prices for sponsored ads. A lot of different factors are affecting the prices. For example, , a lot of influencers have considerably cut their rates. So, it’s important to track the accepted costs on the internet and make arrangements accordingly. during the COVID-19 pandemic A big data analysis on social media can be helpful to clearly know what prices your competitors or niche customers are agreeing at. Social media strategy when using big data If you want to make sure that your big data approach will lead to a higher ROI on social media, you need to have an efficient strategy. Without a strategy, you don’t know what exactly you want from the unstructured data on social channels. Therefore, you’ll waste your time and money without generating considerable leads and boosting sales. A common social media strategy usually comprise the below steps: Market research Defining SMART goals Identifying the audience Choosing the right platforms Generating relevant content Scheduling posts and establishing a social presence Engaging with the community Influencer marketing Analyzing the performance This strategy should help you achieve certain goals which usually contain below items: Drive traffic to your site Get higher conversions rates Build brand awareness Make you appear like a niche leader Additionally, you’ll need certain metrics to analyze your performance and show you how well you’re achieving these goals. Actually, great use of a is to help you know your social performance. You’ll be able to optimize your social techniques based on this information and make the best out of it. big data strategy Conclusion Big data is one of the newest features of information technology and can be of great use to digital marketers. It was tried to summarize the important aspects of in social media marketing and the benefits it can bring to your campaign. Remember to take advantage of this technology to optimize your social presence and get ahead of the marketing competition. big data analytics

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Cryptocurrency trading is rising in popularity, but that doesn’t mean that it’s easy to get started. Successful crypto investing demands traditional trading skills, a grasp of the way that the new tech works, some knowledge of blockchain, and an . understanding of crypto trading jargon If you got your start back at the beginning of the crypto wave, then everything was new and you weren’t the only one making mistakes. Today, we’ve seen that it’s far harder to turn a profit. But the outlook is not all bleak. There are also a lot more resources, wallets, tools and exchanges with hand-holding features to help you learn what to do in a murky market – the kind of stuff that I wish existed back in the heady days of late 2017 when the charts all looked like hockey sticks. Here are some key differences between the experiences of first-time crypto traders in 2017 and today. More Coins, More Confusion In March 2020, there were . At the end of 2017, there were just over 1,300 crypto coins to choose from. There’s a slight disagreement about whether the final total was or , but whichever way you slice it, there’s a lot more to wrap your head around today. over 5,100 different cryptocurrencies 1,335 1,368 Hundreds of new coins come online all the time, but there are also hundreds disappearing. David W. Perkins, a specialist in macroeconomic policy for the US Congress, “The existence of multiple currencies adds difficulty to buyers and sellers making exchanges; all buyers and sellers must be aware of and continually monitor the value of different currencies relative to each other.” notes that That was no small task three years ago, but it’s about four times harder today. In 2020, you have a far greater risk of investing in a crypto coin that goes up in smoke than you did back in 2017, and you’ll need to learn about far more currencies before you can make an informed choice about the marker as a whole. Mastering Higher Trading Volumes Is Challenging In 2020, there are more coins, more traders, and a higher trading volume than ever before. , professors Leirvik and Le Tran note that “the trading volume in the largest such currencies has grown exponentially.” March 12, 2020 was the busiest trading day in the history of Bitcoin, with taking place on Binance’s exchange alone. Writing for ScienceDirect 146,500 messages per second When you’re new to trading, this activity can easily be overwhelming. You’re still trying to spot trading patterns and learn which events are significant and what those events might signify. When trade volume is so high, you have to put in far more effort to sort the wheat from the chaff, at the same time as keeping track of overall market trends. “The crypto market today is simply bewildering. Trades take place all the time, around the clock and around the world,” says Luka Boškin, CMO of ’s exchange platform. “New traders are in even greater need of educational materials to help them quickly get up to speed about what’s going on in the world of crypto, because the whole thing is moving faster than ever.” NewsCrypto The good news is that there are more tools today that can track and analyze trades for you, identify patterns, and monitor the high-level ebb and flow of the markets to help you to cope. A Higher Market Makes It Harder to Turn a Profit In 2017, bitcoin had its price explosion. Until then, it was a niche trading option, and the markets in general were low. Today, millionaire hedge fund owners are investing in bitcoin. Additionally, general worldwide uncertainty and fiat volatility has made many rush for crypto. Together, these trends have pushed the crypto market far higher, so that any further rises are smaller and less frequent. Although there are more exchanges and investment vehicles to help you buy whole or partial bitcoins today, it’s more challenging to turn a profit. In 2017, an initial $1000 investment might have made a 10% profit in six months, but in 2020, it would only make a 5% profit in the same timespan. When markets were low, it was possible to approach crypto trading in the same way as some people approach stock markets – invest a certain amount of money and wait patiently for the market to rise as the asset matures. Between 2015 and 2017, the crypto market trended steadily upwards, enabling the crypto noob of that era to overlook the fact that crypto trading is essentially speculation, requiring you to make decisions fast and trade fast, and succeed in making a more or less passive profit. In 2020, it’s less forgiving. Strong Crypto Messaging Fuels Unrealistic Expectations Crypto evangelists who want to encourage more people to take crypto seriously and invest in it, combined with rising media buzz in the wake of the 2017 bitcoin transformation, can often create unrealistic expectations among crypto noobs. Before 2017, coin traders were primarily motivated by curiosity and enthusiasm. They were in it for the long haul. But newbies coming to crypto in 2020, after years of hearing all about the potential of the market, bring different assumptions. of the Wolf of All Streets podcast, “In legacy markets, nobody expects to get rich quick. Crypto appeals to people looking to quickly turn a small sum of money into their retirement, which is unrealistic.” Scott Melker comments that New crypto traders are misled into thinking that they can get rich quick by buying altcoins, sometimes deliberately by unscrupulous crypto hypesters. No one who reads up has those expectations about the stock market or investing in gold, and it’s a machine that simply didn’t exist until the end of 2017. 2020 Is a Year of Uncertainty Just like the stock markets, crypto trades are affected by economic and political events. It’s hard to remember a year as volatile as 2020, so it’s inevitable that crypto prices are more unpredictable, more uncertain, and more volatile than they were three years ago. In 2017, when the price of bitcoin and ethereum rose, it turned into a crypto bubble that popped in early 2018. Sure, 2019 saw it rally slowly, but it’s too early to say whether we’ve entered another bubble. We’ll only know for sure when (or if) it pops. However, the community of respected big-picture economists does believe that the mainstream financial markets are in a bubble, and crypto tends to be influenced by major market trends. On the other hand, if central banks’ efforts to keep their currencies afloat start to fail, then it’s possible that altcoins will suddenly see surges in adoption for transactional use cases. 2020 is a Tough Year to Enter Crypto, but It’s Not Impossible All in all, 2020 is proving tough in a number of ways, and crypto trading is no exception. As well as the unknowable impact this unpredictable year could have on the crypto market, crypto beginners today have to master far more coins and a higher trading volume, overcome unrealistic expectations, and struggle to make a profit in a higher market. It’s not an easy time to enter the crypto market, but there’s plenty more support available to smooth the way. Disclosure statement: The author has no relationships with any of the companies mentioned in this article.

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Crypto Noobs of 2017 vs. 2020: Learning to Trade Better Is Getting Harder

This article uses Exercise number 10 on the to teach self JOINs in a beginner-friendly way. Self JOIN SQL ZOO tutorial The only way to understand SQL problems is to understand the data you're dealing with. The whole business of SQL becomes really abstract if you can't visualize the tables somehow. So, the first thing we will do is to understand how the tables in problem no. 10 work. Let's take a look at our database. I'm not going to teach how to write a SQL query as I'm assuming you already know the basics. Rather, I'm going to show how I go about trying to make sense of databases. I divided my thought process into the following steps. 1. SELECT all items If our table has millions of rows, a query that returns all items may take a lot of time to load. You can always use LIMIT 50 or something like that so that your table doesn't take forever to load. In our case, SQL ZOO already only returns the 50 first rows of our query, so we don't have to worry about it. Let's see what that looks like. Alright, and are the keys we used to connect the two tables, that's why they're always the same in every line. We got the name of the stop, the bus and the bus . We learned from an earlier problem that we would usually refer to a bus by their num and company like '124 SMT'. So, by looking at our table we could assume that at the stop in Aberlady we can get the 124 SMT bus. id stop number, company So far so good, but it took me a lot more time to understand what the was. At the beginning of the page, there's a link that takes us to a place where they tell us what every column in the table means. They say is the order of the stops, but I still couldn't visualize what it meant just by looking at the table. Now, the good news for us here is that we're not going to need to use to solve our problem, but I'll still tell you how you can understand it in the next step. pos pos pos 2. Use ORDER BY to understand what is going on If we order by the then by , we'll see that the '1 LRT' bus, for example,  leaves from Leith then goes on a round trip until it gets back to Leith after stopping at 9 other stops. If we go down the table, we see that not all buses go on a round trip as they won't always end up at the same stop where they started. num position As I said, we won't be needing to use for this exercise but it could be useful if we were trying to find, for example,  not only the buses available but also the shortest possible routes. pos Ok, now that we got a clearer understanding of what is going on, let's see what the problem wants us to do. Ok, so, by telling us that we need two buses, we know that there is not a bus that goes straight from Craiglockhart to Lochend. In other words, we need to find the buses that stop at Craiglockhart and have stops in common with the buses that stop at Lochend. Because that's where they can get off and change buses. Ok? I hope that's clear. As I said, it may be hard to visualize it without looking at a map. But hopefully, it's going to get clearer in a second. As with everything, there is a number of ways we can do things. Keep that in mind as we move to the next step. 3. Never forget that a self JOIN creates a new table When you do a self JOIN, you might be tempted to try to visualize it as a table somehow joined to itself. But the way to think about it is as two separate tables that look exactly the same. You join the new one to the side of the first one. Because they are exactly the same, any column can become a key. In other words, you can pick what your primary keys are going to be. That's where the fun starts! Right now, there's only one stop per row, but for the next step, we need another one, our transfer stop. So, here's what we can do: we can connect a new route table to the table we already have ON AND like this: num company, You see, our r2 table got appended to our r1 table adding up all of their columns. Both the r1 and r2 always have the same and (in the same lines) because that's where we joined them. num company We already saw that the '1 LRT' line runs through 11 stops. That's why we can see the stop name repeat for eleven rows at each new stop. In other words, from Leith, you can get to any of those stops listed on the far-right column. Let's reduce the number of columns we're showing so we can get a better view of our data. 4. With Self JOINs, think horizontally It's easy to get a little lost before you're about to filter your data. It helps if you visualize your tables as a horizontal map. On your left, you have the place from where you're leaving: 'Craiglockhart'. To your right, you'll have—I'll show it very soon—your transfer stop, then your destination. So, let's filter the column by 'Craiglockhart'. name So, what we're looking at now, if we take into consideration the column, is a list of all the stops you can get to leaving from Craiglockhart. stop Now, imagine that we can do the same for Lochend, but instead of having it as the departure, we have it as the arrival. Let's see what that would look like. Now, the column is showing all the stops from where we can get on a bus and get to Lochend. stop In our query before this one, we saw all the stops we could get to leaving from Craiglockhart. In this one, we have all the stops we can leave from to get to Lochend. In other words, all we have to do is join these two tables together. Again, have that in mind: s join tables horizontally—or to the side. There's something called UNION that stacks tables vertically—on top of each other, but JOINs glue them horizontally. Is that bueno? JOIN So, how do we connect these two queries that we just saw? I will show you the long way first and then a shorter syntax. Alright, I still haven't removed the unneeded columns, but let's take a look. We now have four tables and one table—which is showing us the transfer stop. What we have to do now is to filter the stop on r1 by 'Craiglockhart' and the stop in r4 by 'Lochend' and we'll get to our answer. To do that, we could JOIN another table at the beginning of our table and append another to the end of our table. But, instead, we can use what we learned with subqueries, like so. route stops stops stops We got our solution. How do we know? It says 'too many columns'. So we know we only have to adjust the number of columns being shown. Let's look at the problem header to do so. It says some of the data is still incorrect. Let's investigate why. If we scroll down our table there's a link we can click that shows us what our answer should look like. Let's do that. When we take it to compare our answer to theirs, we realize it's probably just a matter of ordering our columns the way they want us to. That might take a little experimenting in case you can't visualize what columns to ORDER BY right away, but in the end, this is what we should end up with. Yay! We got the smiley face and the solution to our problem. There's only one more thing I'm going to show you which is a shorter syntax for that same solution. Granted, it's not that much shorter and certainly not as intuitive, but there you have it. It's also important to note that when you use the JOIN ... ON syntax you can always write the conditionals on either the ON clause or using the WHERE. That's it. I hope it was helpful. As always, please let me know if you have any questions. Thanks and have fun with SQL!

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Scrum is a buzzword, the virtue signal of choice for middle-management in software organizations. If your goal as a manager is to implement a system by which you: Speed up the of progress appearance Pay for 2x the number of people you need Gather fine-grained data based on meaningless metrics Then Scrum is what you are looking for! exactly , who is not a true Scotsman "Oh you had problems with Scrum at your last employer? Well, that's not real Scrum." - your scrum master Needless to say, we don't use scrum at . Which brings us to our first problem... Qvault Problem #1 - Scrum Is Vague It's hard to criticize Scrum. The idea of "Scrum" in my mind is likely very different from the one you are familiar with. This is by design, and by admission. In the official we find Scrum's definition: Scrum Guide A framework within which people can address complex adaptive problems, while productively and creatively delivering products of the highest possible value. I like to put it more tersely: Scrum (noun) - 1. [software] Any good process that works good Because the definition is so vague, the only thing I'll be able to criticize throughout the rest of my tirade is the common practices of "Scrummers" that I'm familiar with. Hopefully, some of you lovely readers can relate. Problem #2 - The "Sprint" According to the : official guide The heart of Scrum is a Sprint, a time-box of one month or less during which a "Done", useable, and potentially releasable product Increment is created Sprints are useful like achievements in video games are useful; they make us feel warm and fuzzy inside. Motivation is a powerful tool, don't misunderstand me. The problem is that those warm fuzzies are mostly for the sake of . It makes them feel in control and informed. They know exactly what was done and when it was completed. the management team I'm not against management being informed... but at what cost? Sprints require achievable short-term goals. Let's pretend that I'm part of a team that does two-week sprints (because the duration must be consistent) and I'm assigned to build an API that isn't useful until the whole thing is completed. Let's also say that in my head I believe the whole task to take two months if I can work consistently. I need to break the API into pieces that can be completed in 2-week increments. I might be able to get some of the endpoints done in as little as a day or two, but I don't want to miss any of my goals, and I know some of the more difficult logic could take as long as an entire week per endpoint. There are 14 endpoints so I decide on a round figure of 2 endpoints per sprint. An API that could have been completed in will now take almost because I've wasted time putting in along the way. My imposter syndrome starts to set in, but at least management will have pretty burndown charts. 2 months 4 months artificial stopping points Problem #3 - The Scrum Master The Scrum Master is a servant-leader for the Scrum Team. The Scrum Master helps those outside the Scrum Team understand which of their interactions with the Scrum Team are helpful and which aren’t. Depending on how the idea of the scrum master is implemented, it can be a bad idea or a worse one. Let's just talk about what seems to me to be the most common scenario. The scrum master is a non-technical, middle-management type that likes to be in charge of stuff. In addition to all of their development work, the engineers are now interrupted frequently by the scrum master who is asking when the "Java code" for the React app will be done. The very individual whose purpose it is to stop the outside world from bothering their developers is the single biggest bother. In my opinion, non-technical people should rarely, if ever, be managing technical people (except the CEO). I should be able to go to my boss for help and advice with my tasks, or at the very least I should expect them to my assignments. understand Even if the scrum master is a lovable person who grasps the technical issues from a high-level, Too often scrum masters daily tasks involve a stand-up or two in the morning, a meeting with higher-ups in the afternoon, and not much else. Scrum Master isn't a full-time job. If you still feel the need for a "scrum master", just let the lead developers handle the job. They are already at stand-up and likely have a better idea of what is going on. You aren't putting more on their plates, you are likely taking something off. Problem #4 - Estimates Within Scrum, estimates have a primary purpose - to figure out how much work the team can accomplish in a given sprint. If I were to grant that Sprints were a good idea (which I obviously don't believe) then the description of estimates in the official Scrum guide wouldn't be a problem. The problem is that estimates in practice are a bastardization of reality. The Scrum guide is vague on the topic so managers take matters into their own hands. With this in mind, I am again going to criticize some common practices that I have seen in regards to estimates. Fibonacci and T-Shirt Sizes Many super-hip organizations enjoy using the most confusing scales for estimates. They claim that this somehow makes estimating a faster and less stressful process. I remain woefully unconvinced. My first day at a new company during our estimation meeting after hearing they used the dreaded "story points" system: Me: "What is the scale used here for points?" Scrum master: "Fibonacci, where 8 points is the max because we defined it as the amount of work a developer can handle during a two-week sprint". I eventually learned the system. actual 1 point: 0 - 8 hours 2 points: 8 hours - 2.4 days 3 points: 2.4 days - 1 week 5 points: 1 week - 1.5 weeks 8 points: 2 weeks The end goal of an estimate is to convert . Why do we need to add an extra step of ? A simple estimate of "how many days?" would have been easier to think and reason about, while also providing more granularity. workload -> time workload -> story points -> time A common objection to using such a barbarically simple system is: We use fibonacci because its hard to imagine the difference between 7 and 8 days. No one can estimate that closely. Fibonacci sequences go up by ~60% at each step so you aren't forced to get very close to your estimate. To that, I propose base-2 exponentiation based on the scale you care about in the first place, . time 1, 2, 4, 8. Hours, days or weeks. It seems we have solved the problem! Until another good-intentioned scrum master pipes up: If estimates are grounded in measurable time then engineers will feel like they've screwed up if they miss their estimate. Good point, estimating is hard and we don't want anyone to feel like they are a bad engineer just because they aren't the perfect estiamtor. That said, maybe instead of starting a game of "Whose Line Is It Anyway?" the reasonable expectation could be set that estimates are just that, . estimates Estimate - roughly calculate or judge the value, number, quantity, or extent of. If an estimate turns out to be bad it can be re-estimated at to the estimator. no detriment Final Note: Agile != Scrum I'm a fan of agile methodologies and the . I'm not a fan of Scrum. In a later article, I plan to go over my thoughts on what to do in lieu of Scrum while still running an "agile" organization. Agile Manifesto fin. Thanks For Reading Follow us on Twitter if you have any questions or comments @q_vault Take game-like coding courses on Qvault Classroom to our Newsletter for more educational articles Subscribe

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is a weekly no-code newsletter, built using no-code tools like Webflow, Airtable, and Zapier. Working at a , I wanted to learn about insights in the field more broadly, so I spoke with No-Code Report's founder, Parker Thompson, on the state of the industry and its future. No-Code Report no-code analytics firm First off, what does “no-code” mean to you? No-code is all about the ability to create software without the traditional barriers of learning code or hiring dev teams. For me personally, it’s a rapidly evolving community of people who are kind, helpful, and crazy innovative. What made you journey into the no-code industry? I wanted to get into web design last year so I looked for a way to do that on the side. I knew a little HTML/CSS, but wanted to find something easier. I initially used Wordpress with some of the drag-and-drop template editors, but found Webflow after a few months and quickly transitioned to that tool. After discovering Webflow as a tool, I got involved with the Webflow community. I attended the first No Code Conf and really started to experience no-code as a movement. Ever since, I’ve been digging deeper, freelancing, and running No-Code Report. Guy Kawasaki said that Macintosh democratized computers, Google democratized information, eBay democratized commerce, and Canva democratizes design. Tell us about how no-code tools are democratizing various industries. I think no-code tools are primarily democratizing software development. These tools are empowering people to develop software without the need to learn software development. Most commonly, these are things like websites, mobile apps, and software as a service (SaaS). Do you think there will come a time when no-code businesses become the norm - or even, are we already there? If we’re talking about it becoming the norm for businesses to use no-code tools regularly, then I do think that’ll happen. I imagine the term ‘no-code’ will go away and we’ll just see some of these no-code tools and solutions built with no-code tools as software. There are so many industries that will benefit from websites, apps, automations, etc. and no-code is blowing the door wide open for them. What are the major limitations of no-code, or in other words, are there any industries that will always need code? It’s hard to really pinpoint limitations across everything, since they’re pretty specific to each tool. I don’t think many businesses or industries will say “That’s it, we won’t use any code anymore, it’s all no-code from here!” I think there will usually be a mix depending on the use case. The important thing is to weigh the pros and cons. NASA, for example, probably wouldn’t use a no-code tool to launch a rocket, but they use Webflow to prototype websites. What advice do you have for people who want to start a no-code business? I am not a business expert, but I would suggest starting with your business plan. Don’t get caught up in which tools you’ll use and what automations you’ll set up yet. Just think about what your business is at the core and what you’ll need to be successful. No-code tools are a great way to launch fast, iterate often, and maximize your time as an entrepreneur, so you’re in the right place! How will the no-code industry and no-code tools evolve in the future? I think we’ll drop the name no-code eventually and just become a group of software developers using software development tools instead of writing code. I think that’s one of the biggest evolutions we’ll see. Is there anything else you want to share about no-code? Shameless plug, no-code is moving at the speed of light right now. There are new tools all of the time, product updates often, and it can be hard to keep up. I started No-Code Report to make it easier to stay up-to-date without needing to be glued to Twitter. Every Saturday, I send out a high-level summary that should take under 10 minutes to read. If you’re interested, check it out at https://nocode.report

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Motivation A time-series represents the sequence of a variable recorded with time over regular intervals of time. There are various applications of time series like Stock Market Prediction (with daily and hourly data), Annual Sales/Revenue, Seasonal Temperatures changes, monthly Cloud Infrastructure cost and second level prediction of Python has 2 libraries StatsModels and Pyramid that helps to build forecasting models and predict values at a future time. As both these libraries provide forecasts for similar models namely, AR (Auto-Regressive)MA (Moving Average)ARIMA (Auto-Regressive Integrated Moving Average)SARIMA (Seasonal Auto-Regressive Integrated Moving Average) it will be interesting to see the features provided by each of the libraries along with the pros and cons of using each of them. In this blog, I try to summarise the functionalities of both of these libraries by demonstrating the Number of Active Cases for Covid-19 for any Indian state. We keep our scope limited to univariate time series analysis. DataSet The scope of the data is fro 8th March-1st May where data from 8th March-14th April has been used for training and 15th March-1st May has been used for validation and prediction. Here, we have demonstrated using state Maharashtra, however all states data and modeling can be done using the processed data from . https://github.com/sharmi1206/covid-19-analysis STATSMODEL It primarily comprises of three main modules: – Comprises of functions useful for univariate time series analysis – autoregressive models (AR), vector autoregressive models (VAR), and univariate autoregressive moving average models (ARMA), along with Non-linear models like dynamic regression and autoregression. In addition, it also provides autocorrelation, partial autocorrelation function, periodogram, and other statistical properties related to ARMA, and methods that process moving average lag-polynomials. tsa –  Equipped with functionality to model observations at any time instant with unobserved state vectors and irregular components. It has added flexibility to allow estimation with missing observations, forecasting, impulse response functions, etc. This flexibility helps it to differentiate from tsa by estimating additive and multiplicative seasonal effects on models (both on univariate and multi-variate), as well as arbitrary trend polynomials. statespace -Allows simultaneous modeling and analyzing multiple time series. vector_ar ARIMA MODELS An ARIMA model is composed of 3 constituent units which are : : . This part explores any dependent relationship between an observation and some number of lagged variables. AR Autoregression : . This part aims to make time-series stationery by subtracting or differencing an observation from observation at the previous time step of the same time series. I Integrated : This part explores the relationship between an observation and a residual error by application of moving average to lagged observations, with any given time window. MA Moving Average . In order to design a model (say ARIMA) by applying all of the above stated procedures we need to enable all parameters. We can also enable partial parameters and select to choose either AR or MA model. The parameters can be summarized as follows: : The number of lag observations included in the model, also called the lag order. p : The number of times that the raw observations are differenced also called the degree of difference. d : The size or the order of the moving average window. q To start with and in order to have different flavours of ARIMA model, the library imports are: statsmodels.tsa.ar_model AR statsmodels.tsa.arima_model ARIMA statsmodels.tsa.statespace.sarimax SARIMAX statsmodels.graphics.tsaplots plot_acf,plot_pacf from import from import from import from import MANUAL MODEL SELECTION ARIMA The following diagram illustrates the mechanism of using AR/MA/ARIMA/SARIMA by self choosing the model orders (p, q, d) and self tuning it. AR Model This Auto-Regressive model estimates a dependent variable at any timing instant based on some number of lagged observations. The variables can be summarized as follows and formulated by the below-given equation: Yt Y(t-1): Lag 1 of the time series β: Coefficient of lag1 α: Intercept term Dependence of Lag in AR Estimation, where β and α are model estimates Number of Active cases for Covid-19 can be formulated using AR model as follows. Here we put p, i.e. number of lag observations as 2, while d and q are set to 0. model_ar = ARIMA(trainActiveCases, order=( , , ))  
model_ar_fit = model_ar.fit()  

prediction_ar=model_ar_fit.forecast(len(validActiveCases))[ ]

print(model_ar_fit.summary()) residuals = pd.DataFrame(model_ar_fit.resid)
residuals.plot()
plt.show()
residuals.plot(kind= )
plt.show()
print(residuals.describe()) 2 0 0 0 # plot residual errors 'kde' The summary and the predicted output obtained from the model are illustrated below: AR Moel Summary Predicted vs Actual AR MA Model The MA model also estimates a dependent variable Yt based on the lagged forecast errors. MA Estimation with Lagged Errors where the error terms are the errors introduced from respective lags. The errors Yt and Y(t-1) are the errors from the following equations : Number of Active cases for Covid-19 can be formulated using MA model as follows. Here we put ma (moving average window), q as 2, while d and p are set to 0. model_ma = ARIMA(trainActiveCases, order=( , , ))  
model_ma_fit = model_ma.fit()  

prediction_ma=model_ma_fit.forecast(len(validActiveCases))[ ]

print(model_ma_fit.summary()) residuals = pd.DataFrame(model_ma_fit.resid)
residuals.plot()
plt.show()
residuals.plot(kind= )
plt.show()
print(residuals.describe())

model_scores.append(np.sqrt(mean_squared_error(validActiveCases,prediction_ma)))
print( ,np.sqrt(mean_squared_error(validActiveCases,prediction_ma))) 0 0 2 0 # plot residual errors 'kde' "Root Mean Square Error for MA Model: " The summary and the predicted output obtained from the model are illustrated below: MA Model Summary Predicted vs Actual MA ARIMA Model An ARIMA model comes along with both the flavours of AR and MA model where the time series is differenced at least once to make it stationary. The equation can be formulated as follows, where we see the term β coming from AR and ε–the error terms coming from MA model . ARIMA – Differencing + Combination of Parameters from AR and MA model Number of Active cases for Covid-19 can be formulated using MA model as follows. Here we put q i.e the ma (moving average window), d (order of differencing ) and p (number of lag observations) are set to 1. The code snippet for this is : model_arima = ARIMA(trainActiveCases, order=( , , ))  
model_arima_fit = model_arima.fit()  


prediction_arima=model_arima_fit.forecast(len(validActiveCases))[ ]
valid_ml[ ]=list(np.exp(prediction_arima))

print(model_arima_fit.summary()) residuals = pd.DataFrame(model_arima_fit.resid)
residuals.plot()
plt.show()
residuals.plot(kind= )
plt.show()
print(residuals.describe() 1 1 1 0 "ARIMA Model Prediction" # plot residual errors 'kde' Predicted vs Actual ARIMA We can see it’s better to use ARIMA than AR or MA model, as this is the model that closely resembles the actual outcome. SARIMAX Model SARIMAX model is built by extending the ARIMA model, discussed in our previous section. In addition to terms and terms, there are four seasonal elements that are not part of ARIMA that must be configured; they are: AR, I MA : Seasonal autoregressive order. P : Seasonal difference order. D : Seasonal moving average order. Q : The number of time steps for a single seasonal period. m Number of Active cases for Covid-19 can be formulated using the model as follows. Here we put ma (moving average window), d (order of differencing ) and p (number of lag observations) are set to 1. We also enforce seasonal order as (0,0,0,12) to study its behavior, even though Covid-19 does not show any seasonality, evident from research and daily reports. SARIMAX The code snippet for SARIMAX (without exogenous variable) can be given us: model_sarima = sm.tsa.statespace.SARIMAX(trainActiveCases, order=( , , ), seasonal_order=( , , , ),
                                 enforce_stationarity= , enforce_invertibility= )
model_sarima_fit = model_sarima.fit()  


prediction_sarima=model_sarima_fit.forecast(np.shape(validActiveCases)[ ])
valid_ml[ ]=list(np.exp(prediction_sarima))

print(model_sarima_fit.summary()) residuals = pd.DataFrame(model_sarima_fit.resid)
residuals.plot()
plt.show()
residuals.plot(kind= )
plt.show()
print(residuals.describe()) 1 1 1 0 0 0 0 False False 0 "SARIMA Model Prediction" # plot residual errors 'kde' The model summary and the predicted outcome are illustrated from the below plots. SARIMAX Model Summary Predicted vs Actual SARIMA In order to plot the trained, validation and predicted data under proper dates, we use the following code snippet. plt.figure(figsize=( , ))

index= pd.date_range(start=train_dates[ ], periods=len(train_dates), freq= )
valid_index = pd.date_range(start=valid_dates[ ], periods=len(valid_dates), freq= )

train_active =  pd.Series(train_ml[ ].values, index)
valid_active =  pd.Series(valid_ml[ ].values, valid_index)
pred_active =  pd.Series(prediction_ar, valid_index)

f, ax = plt.subplots( , , figsize=( , ))
plt.plot(train_active, marker= ,color= ,label = )
plt.plot(valid_active, marker= ,color= ,label = )
plt.plot(pred_active, marker= ,color= ,label = )

plt.legend()
plt.xlabel( )
plt.ylabel( )
plt.title( + stateName) 10 5 0 'D' 0 'D' 'Active Cases' 'Active Cases' 1 1 12 10 'o' 'blue' "Train Data Set" 'o' 'green' "Valid Data Set" 'o' 'red' "Predicted ARIMA/SARIMAX" "Date Time" 'Active Cases' "Active Cases ARIMA/SARIMAX Model Forecasting for state " Auto-Correlation Plots Differencing helps to make time-series stationary. In order to find a right order of differencing, we use the ACF plot and see that it reaches zero, fast and with a fairly static mean. With Covid-19 data for state Maharashtra, the ACF plot and the code snippet are given below. fig, axes = plt.subplots( , , sharex= , figsize=( , ))
axes[ , ].plot(df_per_State_features[ ]); axes[ , ].set_title( )
plot_acf(df_per_State_features[ ], ax=axes[ , ]) axes[ , ].plot(df_per_State_features[ ].diff()); axes[ , ].set_title( )
plot_acf(df_per_State_features[ ].diff().dropna(), ax=axes[ , ]) axes[ , ].plot(df_per_State_features[ ].diff().diff()); axes[ , ].set_title( )
plot_acf(df_per_State_features[ ].diff().diff().dropna(), ax=axes[ , ])

plt.show() # Original Series 3 2 True 10 5 0 0 'Active Cases' 0 0 'Original Series' 'Active Cases' 0 1 # 1st Differencing 1 0 'Active Cases' 1 0 '1st Order Differencing' 'Active Cases' 1 1 # 2nd Differencing 2 0 'Active Cases' 2 0 '2nd Order Differencing' 'Active Cases' 2 1 AUTO ARIMA MODELS This library automatically discovers the optimal order for an ARIMA model with stepwise execution of hyperparameters and parallel fitting of models. This objective of this library (auto_arima) is to identify the most optimal parameters for an ARIMA/SARIMA and return a fitted ARIMA model. It does not depend on the , but instead, it conducts differencing tests (i.e., Kwiatkowski–Phillips–Schmidt–Shin, Augmented Dickey-Fuller or Phillips–Perron) on its own to determine the order of differencing. PACF/Auto-Correlation (manual computation of differencing) One other difference from Stats Model’s Vanilla ARIMA is that in case the model does not converge, it raises ValueError to signify the re-evaluation of stationarity-inducing measures. For seasonality, SARIMA identifies the optimal P and Q hyperparameters after conducting the Canova-Hansen to determine the optimal order of seasonal differencing , so that the auto-regressive/moving average portions of the seasonal model are defined by start_P, start_Q, max_P, max_Q D The model is fitted within ranges of defined start_p order (or number of time lags for AR), max_p, start_q (order of the moving average MA), max_q ranges. Hence it can be formulated as : (p, q, d)x(P, Q, D) The best model is obtained by optimizing ( – Akaike Information Criterion, – Corrected Akaike Information Criterion, – Bayesian Information Criterion, – Hannan-Quinn Information Criterion, or “out of bag”–for validation scoring–respectively to a minimal value. information_criterion AIC AICC BIC HQIC It also operates with variables (just like state space methods/models) for predicting added features in the regression operation. exogenous Summary of AR with Auto-ARIMA The following code and figure depicts AR model with Auto ARIMA with start_p=0, start_q=2 (by default), max_p=5, max_q=0 model_ar= auto_arima(trainActiveCases,trace= , error_action= , start_p= ,start_q= ,max_p= ,max_q= ,
                   suppress_warnings= ,stepwise= ,seasonal= )
model_ar_fit = model_ar.fit(trainActiveCases)
prediction_ar=model_ar_fit.predict(len(validActiveCases))

print(model_ar_fit.summary())
plt.figure(figsize=( , )) residuals = pd.DataFrame(model_ar_fit.resid())
model_ar_fit.plot_diagnostics()
plt.show()
residuals.plot(kind= )
plt.show() True 'ignore' 0 0 5 0 True False False 10 10 # plot residual errors 'kde' Predicted vs Actual AR Auto-ARIMA Now let's look at the Moving Average model by changing (set to 5). Here's the code snippet for it. start_p (AutoRegressive Moving part - set to 0), start_q, max_p, max_q model_ma= auto_arima(trainActiveCases,trace= , error_action= , start_p= ,start_q= ,max_p= ,max_q= ,
                   suppress_warnings= ,stepwise= ,seasonal= )
model_ma_fit = model_ma.fit(trainActiveCases)
prediction_ma=model_ma_fit.predict(len(validActiveCases))

print(model_ma_fit.summary())
plt.figure(figsize=( , )) residuals = pd.DataFrame(model_ma_fit.resid())
model_ma_fit.plot_diagnostics()
plt.show()
residuals.plot(kind= )
plt.show() True 'ignore' 0 0 0 5 True False False 10 10 # plot residual errors 'kde' The hyper-parameter tuning for evaluating the lowest and best AIC with the residual components are given below. Summary of MA with Auto-ARIMA Predicted vs Actual MA Auto-ARIMA The Auto ARIMA is then used to model ARIMA by using the following parameters ------------------ as shown in the below code snippet. (start_p=1,start_q=1,max_p=5,max_q=5) model_arima= auto_arima(trainActiveCases,trace= , error_action= , start_p= ,start_q= ,max_p= ,max_q= ,
                   suppress_warnings= ,stepwise= ,seasonal= )
model_arima_fit = model_arima.fit(trainActiveCases)
prediction_arima=model_arima_fit.predict(len(validActiveCases))

print(model_arima_fit.summary())
plt.figure(figsize=( , )) residuals = pd.DataFrame(model_arima_fit.resid())
model_arima_fit.plot_diagnostics()
plt.show()
residuals.plot(kind= )
plt.show() True 'ignore' 1 1 5 5 True False False 10 10 # plot residual errors 'kde' Summary of ARIMA with Auto-ARIMA Predicted vs Actual Auto-ARIMA AUTO SARIMA MODEL The SARIMA model is tuned with to find the best model with the lowest AIC. The code snippet is given below, which does parameter tuning for Here and are tuned with values (1,0,1), (1,0,0),  (0,0,1)  and 12 respectively. hyper-parameters (p, q, d)x(P, Q, D) (P, Q, D) (m) The parameters are initialized as , . even , takes start_p=0,start_q=2,max_p=5,max_q=5,m=12 start_q set to 0 default value of 2. model_sarima= auto_arima(trainActiveCases,trace= , error_action= , 
                         start_p= ,start_q= ,max_p= ,max_q= ,m= ,
                   suppress_warnings= ,stepwise= ,seasonal= )
model_sarima_fit = model_sarima.fit(trainActiveCases)
prediction_sarima=model_sarima_fit.predict(len(validActiveCases))

print(model_sarima_fit.summary())
plt.figure(figsize=( , )) residuals = pd.DataFrame(model_sarima_fit.resid())
model_sarima_fit.plot_diagnostics()
plt.show()
residuals.plot(kind= )
plt.show() True 'ignore' 0 2 5 5 12 True True True 10 10 # plot residual errors 'kde' Summary of SARIMA with Auto-SARIMA Predicted vs Actual Auto-SARIMA Seasonal Differencing SARIMA We also try to explore seasonality with Covid-19 dataset by applying regular differencing, where the values are differenced from the previous season. In the equation of SARIMA(p,d,q)x(P,D,Q): P denotes Seasonal AR, D denote Seasonal Order of seasonal differencing and Q denotes Seasonal Moving Average, x is the frequency of the time series. If a model has defined seasonal patterns, we set D=1 for a given frequency ‘x’. For a SARIMA model, we keep the total differencing + D’ <=2 SELECTION OF BEST MODEL with AUTO-ARIMA The following figure illustrates how to select the best Auto ARIMA Model, compute its error metrics for any input time-series data. Comparative Study of RMSE Conclusion and Future Work More work needs to be done by studying the impact of the number of people quarantined, hospital beds, icu units, ventilators, rate of tests done by using Vector Autoregressive Moving-Average with eXogenous regressors (VARMAX). Evaluate the model performance by (multiplicative models) and the two different modules of StatsModel. sm.tsa.statespace.ExponentialSmoothing sm.tsa.ExponentialSmoothing (linear model), i.e. A detailed study of using different smoothing techniques with latency and accuracy to analyze the tradeoff between the two. Evaluate confidence intervals for forecasts, based on an assumption of Gaussian errors as provided by Analyzing the performance impact by concentrating initial values out of the objective function, particularly in situations when the seasonal periodicity is large. sm.tsa.statespace.ExponentialSmoothing With more number of COVID-19 cases evolving, the right order of differencing (if needed multiple orders of differencing) needs to be computed to arrive at a near-stationary series (ACF plot nearing zero). Here we have only computed RMSE, but an ideal situation all error metrics Mean Absolute Percentage Error (MAPE), Mean Error (ME), Mean Absolute Error (MAE), Mean Percentage Error (MPE), Root Mean Squared Error (RMSE), Lag 1 Autocorrelation of Error (ACF1), Correlation between the Actual and the Forecast (core), Min-Max Error (min-max) needs to be computed. The complete source code is available at https://github.com/sharmi1206/covid-19-analysis References https://www.statsmodels.org/dev/user-guide.html#time-series-analysis http://alkaline-ml.com/pmdarima/0.9.0/modules/generated/pyramid.arima.auto_arima.html https://www.machinelearningplus.com/time-series/arima-model-time-series-forecasting-python/ https://machinelearningmastery.com/how-to-grid-search-sarima-model-hyperparameters-for-time-series-forecasting-in-python/https://otexts.com/fpp2/arima-r.html

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Basic Understanding of ARIMA/SARIMA vs Auto ARIMA/SARIMA using Covid-19 Data Predictions

At first I was a little overwhelmed when I approached the Firefox-voice repository because I had very little experience working with such a large codebase, the code base with a lot of people making contributions. I had to spend a lot of time to setting up communication, running the project locally (with the help of project Readme). I had to spend a very good amount of time understanding the directories, and how to set up the Project on my local machine just to get the application to run. It was really challenging to get this project running at first, I was about to give up but again thanks to the mentor for a fine readme which was helpful in setting this project up and running. As a beginner or someone not familiar with the terms and project niche, it was really hard for me to understand the actual purpose of the project. PULL REQUEST #1 : This issue helps me to get a basic knowledge of the Project. Set Minimum Node Version: https://github.com/mozilla/firefox-voice/pull/1210 This was a fairly simple issue in which i have to set the minimum version of NodeJS. At first I added ‘engineStrict’ but my mentor assure me that ‘engineStrict’ is only used when you have a clear idea about the latest version to use. So immediately I removed it from the code and I set the Nodejs minimum version.After Successfully landing my first PR I jumped over the next issue.. I learned to code in Large codebase for the very first time! I spent hours fighting with GIT and making multiple experiments to make my first PR. I am grateful to the mentor for letting me explore and do things at my own and let me learn about more powerful git features. PULL REQUEST #2: In this issue I learned about intent and it’s working in the Firefox-voice project. Add more examples to Door hanger/pop-up: https://github.com/mozilla/firefox-voice/pull/1383 In this issue I have to add examples so they will appear randomly on the Door hanger.To fix the issue I added the given phrases to the existing list of examples that is displayed in the Door hanger/popup to educate users about the things they can say. First given phrase is “Find spaghetti on page” So i put this phrase in the relevant intent which is “find on page” to appear on pop-up. Second phrase is “count my open tabs” So I put it in the relevant intent which is “count tabs” to appear on Door hanger/pop-up.Third phrase is about “open downloads” So I also put it in the relevant but intent is “Downloads”.The First 2 phrases added into the same intent file while the Last one is fixed in different intent file. After doing Good first issues I jumped over to fix some bugs. PULL REQUEST #3 Command transcription for a long string is cut off in negative feedback display: This issue was bit trickier and introduced me the new concepts of . CSS https://github.com/mozilla/firefox-voice/pull/1476 This issue is about Command transcription for a long string is cut off in negative feedback display. In order to fix this bug Firstly, I made changes to the existing CSS property “White-space” but after asking for more clarification about the issue I have found that the long string is still cut-off in negative feedback display. So I decided to add Few more CSS properties in feedback header to prevent the cut-off of a long string in negative feedback display. My overall experience comprises of nervousness, excitement, happiness, confidence, frustration, learning, competing, solving different challenges, understanding project and learning new concepts and much more. This is the month where even my weekends were productive. All mentors and contributors are always helping and motivating, celebrates even a small achievement not making us feel dumb at all. My experience is great up till now I’m looking forward to contributing more.

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How I Started an Open Source Contribution to Firefox-Voice Repository

For six-months (and counting) COVID-19 has accelerated the need for SMBs to leverage UCaaS (unified communications as a service), forcing executives to jump into one of the fastest-growing segments in the supply chain. UCaaS is a cloud delivery model that offers a variety of communication and collaboration applications and services, including providers such as RingCentral, Nextiva, 8x8 Inc., and Microsoft, to third-party cloud service providers, such as Verizon, AT&T, and BT. For the uninitiated, UCaaS was born out of four distinct technological phases that drove the need to have unified communications: The Rise of the Phone and E-mail For a long time, a company’s electronic communications consisted of two main parts--the phone and e-mail, thanks to the rise of the Internet. Having both a phone and Internet, allowed for a business to literally "be connected" to the rest of the world in a single location (before the Internet expanded to infinite locations). As technology has evolved since the 1990's, the communication needs of businesses and the average entrepreneur have grown. With the voluminous amount of information being shared and distributed on a daily basis, tracking and locating where information is coming from is essential to complying with data privacy laws, but also staying vigilant and organized. A one-stop-shop of information coming in and out would eventually be a universal demand. #3 - Instant Messaging (yes, ICQ and AIM) Millennials everywhere know instant messaging (IM) was a game-changer for the ways in which they communicated with family and friends. Instant messaging grew tremendously from the late 1990s (thanks to AOL) onward, when a small Israeli-based team, Mirabilis, made , the very first instant messaging platform publicly available. ICQ A year after ICQ was made available, AOL released its IM platform, AOL Instant Messenger (AIM). And here we are 23-years later with Facebook Messenger (just without the buddy list and endless variations of a screen name that a person could create). #4 - VOIP/Video Conferencing Platforms (Skype, Zoom, etc) Since IM took off, it paved the way for new technologies like e-mail, phone calls, group chats and video conferencing to take place, making it possible for remote communication from anywhere in the world, with very little centralization. What we basically ended up with was a number of communication channels coming from every direction without being able to group the information in a single location. Thus the idea for UCaaS was born. How Our Biggest Communication Platforms Are Using UCaaS UCaaS offers the opportunity to integrate multiple communication methods through a single cloud provider, including enterprise messaging, telephone communication, and video conferencing, which facilitates team communication. Think about the Slack and Microsoft Teams messaging platforms. This type of platform can then be integrated into call center services, such as call routing, and call centers, with additional functionality when combined with phone dialing software such as Avaya, Vonage, RingCentral, among others. One of the leading companies out there, Nextiva, a voice-over-internet-protocol (VOIP) company and UCaaS SMB specialist , Eric Martorano as the company’s newest Chief Revenue Officer, who will be overseeing Nextiva’s global revenue strategy and go-to-market strategy initiatives as he leads Nextiva’s sales organization. announced that it has appointed Microsoft’s former general manager Bringing to the table his extensive experience with Microsoft in leading direct and indirect sales and marketing teams, executing high-growth channel and distribution strategies, and taking industry-leading products to market, Martorano intends to take on his competitors as the global coronavirus pandemic continues. “We go head-to-head every day with RingCentral, 8x8, Vonage, and they have pretty solid solutions, but the Nextiva solution just fits better squarely with the SMB customer,” said Martorano, Nextiva’s new CRO effective today. “It was built with the SMB customer in mind. It has the ability to scale upwards into the enterprise, but one of the differentiating factors with Nextiva is when we build our products, we think about how we can make a difference with the SMB customer. … I do feel like Nextiva has something that Intermedia doesn’t with our NextOS. When you take a look at what we’re bringing to market, this is something special that the channel is going to really embrace.” Prior to leaving Microsoft, Martorano served as the CEO of Accordo Group, which was recently acquired by MarketStar. Currently, he sits on the Board of Directors for Velosio, one of the largest Microsoft Dynamics 365 partners worldwide. In a brief conversation with Nextiva’s CEO, Tomas Gorny, the company expressed excitement as Martorano joins the team, sharing that “as we continue to bring innovative products to the market, we look forward to Eric focusing on scaling our sales organization and our partner community, two important areas that will help accelerate our innovation in connected communication.”

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Nextiva Takes Huge Step Growing Sales Channel With Addition of Microsoft’s Former GM, Eric Martorano

Do you know what surprises me the most in this whole lead generation business? As the CMO of high-quality data sets , I find it hard to believe that there are still marketers and sales teams out there who are oblivious to the astounding impact of data to sales performance. provider It has been known for a while now, that the right data is a rocket fuel to lead generation, helping to identify potential clients with laser precision. The use of data is so effective that the switched-on marketing and sales team leads don’t even blink before assigning the largest chunk of their budget to it. Don’t just take my word for it. Let’s look at the latest . facts First, the use of data-driven automation software has been skyrocketing in popularity among marketers. According to the reports, 80% of them acknowledge that using data had a positive effect on increasing conversions. Not to mention the astounding effect it has on the enhancement of sales platforms. And yet, 61% of the professionals in the field still admit that generating traffic and leads are their greatest challenge, as reported by . And, for all of you in those 61%, I have your back. Read on. HubSpot Why reliance on data has become unavoidable It is no surprise that fierce competition between companies is urging to reach higher sales targets each year. So, to consistently outperform your game and fierce competition, it is impossible to avoid thinking about more effective strategies. What happens most often is that marketers and sales officers choose to take the human element out of the most repetitive and time-consuming tasks. The manual labor behind lead generation, besides being a complex and lengthy process, also poses a risk of low accuracy and reliability. Since the relevance of information changes fast, it often goes out of date as soon as it reaches the company’s systems, such as sales platforms. These issues can hinder growth as unreliable data makes it impossible for the decision-makers to pinpoint the leads that are worth the investment of time and effort. This realization turns into the first step towards the death of the traditional lead generation approach of using manpower. The only logical solution known to date is to entrust these tasks to data-driven AI. The unbeatable power of data Why AI you ask? Well, the reasons are plentiful. Appropriate integrated technologies can offer the right insights to target the right profiles at the right time with the right message. In fact, algorithms propelled by reliable data prove to be unstoppable when it comes to sourcing contacts who would gain the most value from the product or service. To be more specific, let’s look at the main three advantages arising from data-driven lead generation. First, the reliability of collected data is higher as information can be continuously refreshed in real-time, and there is less space of human error. Second, with the help of the computing power, hours spent screening and evaluating potential target accounts are reduced to the minimum. And third, employing data-driven approaches to marketing and sales provides a broader understanding of the overall size of the target pool and its positioning online. Data is wanting to be collected Okay, once you are convinced about the benefits of automating lead generation, the natural question is then where to find the data to fuel your systems. Think like an expert marketer. Where can you find publicly available information such as age, gender, academic and professional background, attitudes, and preferences to find your leads? Where are people willingly sharing all this information for all the world to see? Of course, it’s social media. All this gathered intelligence provides valuable insights to target with precision. Also, social media platforms can be a great space to keep people engaged and informed on the latest offers or company news. Marketing reports back it up also, naming social media marketing as the to improve lead generation quality. most effective way Going deeper to various types of social channels, that Facebook is considered an essential part of marketing, especially after the introduction of Lead Ads function. we can see Also, Twitter should be taken as seriously as well, generating 82% of social media leads. What is even more interesting is that LinkedIn has the power to generate more than of B2B leads. 80% The hard truth is that the full social media potential to increase sales has not been fully realized yet. For instance, only 47% of marketers take advantage of its LinkedIn. In my opinion, the reason behind this dormant potential is the scary topic of information extraction. Most marketers are scared of this concept, not knowing where to even begin to comprehend the process. I can help you out with this too. Easiest ways to obtain data So how to obtain the right data? Of course, there is always an option to build a complex IT infrastructure and hire a few proxy savvy specialists to figure out this famously difficult data extraction procedure. However, that’s not the most popular way to go about it. Nor the easiest. In my experience, I can say that there are plenty of companies that offer high-quality public data collected from various websites. The tricky part is to distinguish the most valuable data sets from all the available information out there. A good rule of thumb is to keep an eye on the following aspects: First, the data must be continuously updated to provide insights that reflect the current reality. Otherwise, you will be making decisions based on yesterday's news. Second, the information needs to be ready to use. This means that the data sets have to be parsed - delivered in a format that is ready for analysis. This will save you loads of time. And third, the data points have to be ample, reliable, and accurate. There are a few of data providers out there which tick of all the necessary boxes. But identifying them is no easy task, and don’t expect your rivals to give you any clues either. : obtain a data sample first from a provider before committing to longer-term partnership. Once you feel their product, you’ll know just how much further potential you will be able to unlock. Here is my pro tip Where will lead generation lead next? As a marketer myself, I can say that we are good followers. For decades now, marketers have followed their target audiences from cold calls on the phone to emails and now - to online platforms. As my last insights on this article, I would say this, social media is the most targeting-friendly outlet to generate leads and will continue to be so in the foreseeable future. This becomes even more obvious observing the fast growth of the influencer industry, reaching the value of nearly in 2019. $2.5 billion Also, to fully acknowledge the transition to smartphone browsing, it is important to note that the most successful tactics for lead generation will be the ones offering frictionless and timeless user experience.

Blink

Data's Impact on Traditional Lead Generation

Building a community can indeed provide a moat. But–I find many companies/brands/creators profess to have community, when they really just have customers or followers. To have a truly defensible community, I believe the following need to be present: high intentionality, P2P interactions, & UGC content. Hallmarks of “real” community: : Members seek out the community as a destination, not just as part of a broader platform’s feed Intentionality : Strong engagement and ties between members P2P interactions : Members contribute content vs. just engaging w/ what’s broadcasted to them UGC content More thoughts on community: Originally published as “ Not all communities are created equal "

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