We are on a mission to decipher language, which is the most complex type of data that ever existed

Dashbot

dashbot

Introduction With conversational products and interfaces, product creators now have to imagine an interaction where the screen plays an ancillary role. As a consequence, the majority of the best practices and principles of a good user experience need to be redefined, if at all used. Even within conversational interfaces, we don’t speak same way we write. We don’t pronounce all words in the sentence, combine words, don’t say some words at all and huge part of our communication is non-verbal. Hence the MVP for conversational interfaces needs to be different from that for any other product. It’s needed to set good expectations of what it can do for a user. Build Out Conversations, Not User Stories In my experience, building user stories for conversational interfaces turns out very clunky, and a better approach is to build out possible conversations between the end user and the product. Focusing on the bookends of the conversations helps you to understand the trigger and the goal. Improving the user experience provides customers the solution to their problems with as little friction as possible. Improving confidence levels and increasing the scope of utterances is the key way to reduce friction for conversational UI. From learning all the different ways that someone may ask for their account balance, to increasing the number of tasks that can be performed autonomously, every challenging question that a customer asks is an opportunity for us to learn and improve. Here are some of the things to keep in mind when building out these conversations: High-level flows Once you have a few sample dialogs, you can abstract the flow and logic of the conversation. This provides the structure of your conversational interface. Good designs balance the need for clearly defined user paths with the users’ desire for shortcuts directly to what they want. Start with the most ideal or optimal path that you envisage with the users. This is perfect alignment between customer actions and your designed intent. Then expand the path as you go along. Adapt to What Users would Naturally Say The beauty of conversational interfaces is that it comes naturally to users and they don’t have to learn how to use them. The product should to adapt to the user’s word choices, instead of forcing the user to memorize a set of commands. It’s easier, and more natural, for users to respond to a narrow-focus question (e.g., “Does that work for you?”) than to be taught what to say (e.g., “If that works, say ‘yes.”). Provide Cues A bot should drive the conversation forward and at times even restrict it. There are some easy ways to help the user stay within guardrails. Visually, you can use buttons or quick replies (FB Messenger and Slack supports this) to nudge them in the right direction. Consider suggesting things to do; this will help users discover additional functionality. “Hey bot, book a table.” “Table reserved. Would you like me to order an Uber?”. Bot interactions are a bit like the traditional e-commerce flows. We should constantly keep the user updated and help them move forward, while avoiding overwhelming the user with a wall of information. Interactions Should Be Simple The number of paths a conversation can take increases the potential for dead ends. It is better to limit the functionality and nudge the user down a particular path. A simple solution is to use structured messages to guide the users. Rather than asking the end user to type “yes” or “no,” show a structured message with two buttons. Focus on Spoken Conversations When starting, it is better to focus on just the spoken conversation, without the technical distractions of code notation, complex flow diagrams, screen size etc. Getting the flow right is easier if everything is in one place. As you expand to other devices like mobile phones, pieces will move out of the spoken prompts and into the display prompts, chips, and visuals. Handling errors Conversational interfaces can face the following 3 types of errors: No Input: The product did not record the user’s input. System error: Error in fulfilment of the user prompt. No Match: The Action couldn’t interpret the user’s response in context. ‘No Match’ error is a little trickier and needs to be handled well in the conversations. Here are a few possible causes of No Match errors. Prompt: What time works for you? User: Sometime late in the evening? Prompt: Sorry, what time? (The user says something relevant to the context, but the product doesn’t understand it.) Prompt: What time works for you? User: What’s the weather like? Prompt: Sorry, what time? (The user wants to switch topics entirely.) In each context, it is important consider why the user might be having difficulty. Then, in the subsequent prompt, include additional support in the form of options or additional information. E.g. Prompt: What time works for you? User: Sometime late in the evening? Prompt: Sorry, we have two time slots. One in the afternoon between 1 pm and 2 pm and the other in evening between 4 pm and 5 pm. Now, what works for you. If there is a ‘No Match’ even after the second attempt, end the conversation to avoid further user frustration and offer a substitute or alternative method for follow up. E.g. Prompt: Sorry, I’m still having trouble, so you may want to visit our website instead. Good error handling is context-specific. Even though you’re asking for the same information, the conversational context is different on the second or third attempt. In order to play the right error prompt for the context, you’ll need to keep track of how many, and what type of, errors have occurred. Randomize Prompts When Appropriate Craft a variety of responses just like a person would. This makes the conversation feel more natural and keeps the experience from getting stale. E.g. randomize your first prompt with Hi, Hello, Hey, Welcome etc. Right mix of Conversational Components Conversational components are all the things that make up a prompt, like acknowledgements or questions. They also include chips, which are used to continue or pivot the conversation. Prompts and chips are the core of the conversational interaction and should be designed for every turn in the dialog. lists out the different conversational components that can be used in a prompt. Design guidelines with Google Be concise and relevant The conversational interface is also linear, and unlike GUIs, there’s no way to skim over the information. By forcing users to uninformative and irrelevant verbiage, you are unnecessarily wasting their time and testing their patience. People do not appreciate taking extra time or jumping through hoops to find things out or to get things done. Successful conversational interface design therefore should be brief and concise. Graceful Exits Make sure that the user can leave the current conversation flow. Whether it’s typing “quit”, timing out, or even erroring out. The bot should always allow you to exit gracefully without making the user feel guilty. All About Context Once you have generated potential use cases and filtered them against real business goals, you next need to answer a few questions about your target users, such as the customer’s identity, feedback, the channel used for contact, date, time, location, and other information in real time. All these questions will influence the implementation of a conversational interface experience. By analyzing all that data using artificial intelligence and machine learning, the bot can anticipate customer needs. In 2D design contexts, you can watch a user interact with your app — scrolling, tapping buttons, typing but in conversational product design, you have to look at the broader user context. Intent is easier to express through words than a hamburger menu, but natural language is harder to interpret than a click. Over time, it gets easier by understanding context and observing user behavior. It is one thing to train humans to input commands that a computer understands. It is a completely other process to teach a computer to map natural human language inputs to intent. Mapping natural language to intent is the first layer to conversational UI. Leverage Platform Capabilities Bots are completely different from platform to platform as well. All the platforms have different functionality. They all have different feature sets or capabilities. Alexa is a voice-first experience. Alexa’s versions of apps are called ‘skills’ — the idea being that you can teach your Alexa to do something new by enabling a new ‘skill’, created by a third party. Google’s Assistant is more of a platform: ‘Actions’ (Google’s version of ‘skills’) can be either voice-activated, tapped on or typed to. A hybrid voice, text and type interface, Assistant lets you use whatever method suits you in your current context and move between methods seamlessly. This also means Assistant is available on a wider range of form factors, from smart speakers to watches to smartphones to TVs. Facebook Messenger is a chat platform, augmented with a wide selection of customisable widgets allowing users to shortcut conversations and quickly get stuff done. It’s really easy to bring a Messenger chatbot into a human conversation to help you get stuff done. A conversational product should try to get the most out of the platform it is on. Not just NLP, but also prediction engine When one person asks another a question, it takes an average of 200 milliseconds for them to respond. This is so fast that we can’t even hear the pause. In fact, it’s faster than our brains actually work. It takes the brain about half a second to retrieve the words to say something, which means that in conversation, one person is gearing up to speak before the other is even finished. By listening to the tone, grammar, and content of another’s speech, we can predict when they’ll be done Monitor Health of the Bot The older analytics tools out there don’t cut it when it comes to bots, so it’s important to do a deep dive and not just plug in something off-the-shelf. There are new players, like Botmetrics and Dashbot, who are building the tools for bots from first principles, and they are improving everyday. But even they may not provide all the information / functionality you need, and you might end up with your data being silo-ed and inaccessible. The entire funnel is wrought with ways for things to go wrong. Given this range of possible user inputs, bots often misinterpret or simply can’t determine what the user wants. Examine the previous prompts to see where you could make some clarifications. Was the call to action clear? Confusion Triggers: Knowing the average conversation steps enable you to start segmenting good or bad experiences between the user and the bot. A conversation step is a single back-and-forth exchange between user and bot. Your average steps will be different depending on the type of the bot. Conversations that either significantly exceed or fall short of the average conversation step usually indicate a bad user experience. Either a user gave up too quickly or a bot took too long to complete a user’s goal. Conversation Steps: Conversation Flow: Pay attention to the way users naturally ask for things. Does the flow make users feel like they can only provide one piece of information at a time, or does it encourage them to provide multiple details in one sentence? Look for places where users look confused or are unsure of what to say or do. Users might say something you didn’t expect. Take note of it and add handling for it in your design. Signs of frustration or impatience show that the interaction is too long-winded. Review your prompts to see if you can be more concise. Observe who’s speaking the most and whether users seem to be in control of the conversation : Associated with the number of average steps is the average number of conversations per user. This indicates engagement with the bot. 4. Conversations Per User : If your bot supports both push and pull interactions, then you will want to compare the differences in how users interact with your bot. Active users will consume messages sent by the bot, whereas engaged users will respond. This is important because you can learn from users who are engaged. These are your happy users that are leaning into the experience. You will want to accommodate these types of conversations. 5. Active vs. Engaged Users : Know how long it takes for your bot to respond. Know the latency period between command and response. This impacts the overall user experience. You’re looking for median time as well as outliers here. 6. Response Time A bot should save time and relieve stress by reducing friction and effort. ​Otherwise it is not much better than the website or app that came before it. Integrations and contextual relevancy are key elements to the experience. A Hybrid Experience Is Okay It’s a mistake to believe a conversational design means every user input and output has to be handled in a purely chat format. Chatbots live within messaging apps and users are already accustomed to communicating with friends using text, but text input is not efficient for all use cases. The GUI replaced the text-based terminal for a reason and some tasks like browsing and selecting is faster with touch or click. Whenever it makes sense, it’s fine to consider a hybrid approach and use other interactive elements within the conversation (e.g. buttons, cards, forms) to help users complete their goals faster and with less friction. Over-reliance on structured messages, however, will feel artificial as you lose the conversational element. Conclusion Designing from first principles is the only way to avoid fundamental usability problems especially because it is a whole new paradigm of user experience. It can be a reasonably safe assumption in web or mobile apps because people have learnt the standard UIs and gestures, but not in the conversational interface world. Conversational products relate to delivering service over voice and messaging interfaces, but it also implies a different philosophy when it comes to product development, which is much more about understanding the context, constant iteration and constant A/B testing.

Building Conversational Products & Interfaces

WTF? Am I living in the future? I‘m pretty sure I just experienced the future of money while in Dash’s Slack community, and I have to admit, it was crazy! For those of you who might be confused by certain parts of my title, let me break it down. is an app that allows people to work on projects remotely. It’s used by global teams, companies and organizations. I’m familiar with Slack because when I was a writer for , they used the slack app for communication purposes. It makes organizing and group messaging a lot easier to manage than email. Slack Interesting Engineering I didn’t receive the tip in $USD. I received it in digital cash, called which was equivalent to $60. It’s similar to Bitcoin but has some features that Bitcoin doesn’t have. Dash An electronic wallet is a place where Dash or other digital smart coins can be sent and held. Think of it like an email address, except the content in that address is money, not messages. But it’s kind of the same concept as email as far as the addresses go. It’s a lot more secure than email, though, because it has security features that email doesn’t have. So, how did I find myself in a Slack chat room, telling a robot to send money to my electronic wallet? This sounds insane, doesn’t it? A few days ago I began researching this new digital cash called Dash. I had noticed the price of Dash had gone up a lot recently and I wanted to understand why. Before the recent spike, you could buy one Dash for $20, but now one Dash is worth $60. In other words, if you had purchased 10 Dash when it was $20 each, spending $200, you could sell your 10 Dash for $60 now, which would amount to $600. You would have just made $400 in profit. This sounds crazy doesn’t it? Digital currencies are like start-up companies and they are all competing for your business. What’s their business? Currency. There’s now a market for currency, just like there is for shoes, cars and coffee. These new digital currencies can experience huge growth spurts which makes early investors a lot of money. They can also experience swift declines, too. The main reason I’m seriously looking into Dash is because early Bitcoin pioneers are saying that Dash has huge potential to be embraced by the mainstream. Dash’s organizational structure is more suitable for mainstream adoption because their community has one thing that most digital currency communities lack: cohesion. Even Bitcoin’s community is divided right now, which makes investors and people like me nervous about Bitcoin’s future. I recently wrote a Medium article that explains and also made a that included a segment about Dash. The response I got from the Dash community was overwhelmingly positive. I created a Twitter Moment with the title, which was shared on the official Twitter page. Not long after this I was contacted by a journalist about why I have been buying Dash. And then the next day sent me an invite to Dash’s Slack channel via Twitter. I accepted the invite almost instantaneously, deciding to follow the natural course of synergy. Dash to newbies parody video What is DASH? Dash: Detailed Bloomberg News Tao of Satoshi Anyway, when I arrived into the Dash Slack community, I was welcomed very warmly. My video had been shared in the #dash_talk channel and people seemed honestly amused that I had shown up so quickly to the Slack channel. Slack app logo If you’ve never been in a Slack chat channel before, you should try it out. There are many different kinds of bots in Slack, all of which have different functions. There are welcoming bots, so when a new member enters a chat room, they are welcomed immediately. There are also info bots that provide current stats or data on particular topics. There are bots that can send money to electronic wallets, too. The one I interacted with was called @dashbot and apparently it’s the production version of Tipbot. The bots are mostly friendly and serve some functions that are considered too mundane for humans. So, after my warm welcome and introductory greetings, the Dash community members began doing something that was completely foreign to me: They began sending me tips in the form of Dash digital coins! I was suddenly flooded with many tips, I think from 5 different people. It was crazy! I had no clue what to do with the tips because this was the first time I’d experienced this! Here is what @dashbot said to me: “Hi there @stellabelle, you just received .02 Dash from @UserA ! This message was used to send the tip: tip @stellabelle .02 dash (clapping hands emoticon). tell the bot to withdraw an amount to an address. You can also use all to withdraw your complete balance (minus the transaction fee). @DashBot withdraw 1 DASH to XekiLaxnqpFb2m4NQAEcsKutZcZgcyfo6W I’d never received a digital cash tip before in Slack and I certainly had never told a bot to send me money! After the fifth member sent me a tip, I decided it was time to try telling the bot to send the money to my Dash address. My first attempt wasn’t perfectly executed, but the bot understood what I wanted to do. Here’s the exchange I had with @dashbot: Me: withdraw all DASH to XekiLaxnqpFb2m4NQAEcsKutZcZgcyfo6W @dashbot: @stellabelle we don’t support that currency yet! You want me to withdraw .14 DASH to XekiLaxnqpFb2m4NQAEcsKutZcZgcyfo6W. Is this correct (yes/no)? Me: yes @dashbot: Great! I will continue……. Withdrawal of .139900000 Dash to XekiLaxnqpFb2m4NQAEcsKutZcZgcyfo6W transaction: link here I’m not sure why @dashbot didn’t understand my command, but I was happy to discover that @dashbot was pretty intuitive and knew what I wanted done. The thing I noticed with this bizarre and futuristic experience was that the friction has been completely removed when sending money from person to person. The only thing remotely similar to this would be PayPal, but even with PayPal, you’d still have to log into your account then send your money through PayPal’s website. This new digital cash method didn’t require anyone to log into their account. Instead, it relied on cryptography and private keys. This is a radical idea, if you think about it. This means there’s no financial institution between your money and your friend’s money. There’s only the blockchain which ensures that the transactions are secure and legitimate. And because this blockchain is open and viewable by anyone, it makes it unlike any banking experience you’ve ever had. It’s an exciting new world and I think it’s the future of money. If you’re new to digital currencies, the long string of alphanumerics can look confusing. That’s your wallet address. The wallet address shown above is not my own wallet address. It belongs to the in existence. That wallet contains 257,500 DASH ($16,440,121 USD). Isn’t it weird that you can see this information? This alone should send you deep into the digital cash rabbit hole….. richest Dash wallet Disclaimer: I am invested in Dash, starting from a week ago. I consider myself to be a Dash noob who is learning a lot every day. The Dash community’s welcoming attitude and acceptance of newbies is why I am really excited about it. I might add also that if you go into Dash Slack and expect to get tips, you’re on the wrong track. Expect nothing. Give as much as you can. Technology is only as good as the people who are building it and using it. In the end, it is people, not bots that count the most in building a community worth living in.

I Just Told A Robot To Send a $60 Tip To My Electronic Wallet

It will come as no surprise to those of you reading this (thanks!), that the interest and applications of ‘ ’ is growing rapidly. Amazon Alexa and there is talk around for the next 10,000. I won’t be diving into specifics and discussing issues like . That is not what this post is about. Voice-Assistants recently hit 10,000 skills what will drive adoption retention There are lots of resources & tools, tons of cool products, frameworks, articles and people out there to help you learn about the landscape. 💫 Here are some that I find particularly useful 💫 This post is also on GitHub and open for suggestions, just submit a pull request by VoiceLabs The 2017 Voice Report 🤔 How To Use This : There is very little on the front focusing on Voice-Assistants. does the best one IMO. 📰 News newsletter Matt Hartman ( I’m thinking of starting one too —if you’re interested, sign up below!) : Always interesting to see the companies operating in these spaces. They are broken down into different categories so you can easily jump into ‘Building’, ‘Products’, ‘Analytics’ etc. If you think there are some that need adding, 🍜 Startups tell me here . This is just to outline some companies/funds that are very focused in the space right now. Again, if I’ve missed some worthwhile, 🤑 Funding: tell me here . These are some of the awesome people I follow and have come across. I’ve linked them all, you should check them out. If I’ve missed some worthwhile, you know to 👥 People & Posts: tell me here . Enjoy 😊! 🚀 I’ve launched something: Skills.wtf — A site to find the best Alexa Skills 🚀Also, I’ve added a little note about at the end of this post. A community helping facilitate connections to; an experiment I’m working on - Get a skill made/make skills for people/companies- Find investors active in the field- Intros to other active enthusiasts- Bounce ideas around with others- Advice & mentorship from experienced individuals- Resources and tools to help you build- Discover interesting products and companies 📰 News 🗞 Newsletters _Hearing Voices - This week's news about voice computing apps, delivered directly to your inbox. ..._www.getrevue.co Hearing Voices - Revue The Official Amazon Alexa Developer Newsletter _You have total control over when you want Google Home to respond to your voice commands. Its light states tell you the…_madeby.google.com Made by Google (General Google news + Google Home. Subscribe at bottom of page) 🖥 Websites/Sources _Read writing about Alexa. Every day, thousands of voices read, write, and share important stories on Medium about Alexa…_medium.com Alexa - Medium _Read writing about Voice Assistant. Every day, thousands of voices read, write, and share important stories on Medium…_medium.com Voice Assistant - Medium _Read writing about Amazon Echo. Every day, thousands of voices read, write, and share important stories on Medium about…_medium.com Amazon Echo - Medium _Read writing about Google Home. Every day, thousands of voices read, write, and share important stories on Medium about…_medium.com Google Home - Medium _Read writing about Siri. Every day, thousands of voices read, write, and share important stories on Medium about Siri._medium.com Siri - Medium _Read writing about Voice. Every day, thousands of voices read, write, and share important stories on Medium about Voice…_medium.com Voice - Medium venturebeat.com VoiceAssistants_on_VentureBeat _The brain behind Amazon's voice powered devices like Echo, FireTV etc._www.reddit.com Amazon Alexa * /r/alexa _r/AmazonEcho is a community centered around the Amazon Echo, or as we like to call her - Alexa. Alexa is designed…_www.reddit.com Amazon Echo | A voice command system that brings the Internet Of Things to your home * /r… _Everything Google Home: tips, bugs, new features, requests, etc._www.reddit.com Everything Google Home * /r/googlehome _WIRED is where tomorrow is realized_www.wired.com VoiceAssistant _Crunch Network Even before smartwatches, I did not wear a watch. I did not buy an Apple Watch or Pebble, despite the…_techcrunch.com Alexa | TechCrunch _Google Home is Google's answer to Amazon line's of voice-powered Echo devices. After announcing Home at its I/O…_techcrunch.com google home | TechCrunch _Learn about Voice applications, Amazon Alexa and Google Assistant innovation. A hands-free world is coming, join in!_voicelabs.co Blog _multiplex-past, present, future technology research + insights ☂️_readmultiplex.com @ReadMultiplex _Read the latest Amazon Alexa and Google Assistant news, talking about the newest developments in the Voice-First…_voicelabs.co Press Coverage - Voice-First Industry 📜 General news in space (not Voice specific) _Bringing you the latest in Artificial Intelligence, Robotics, and Neurotechnology_inside.com Technically Sentient _Everything about chatbots. From the makers of BotList_botpublication.com BotPublication _Connecting Technology to the Masses_gomainstrm.com GoMainstrm _Chatbots, AI, NLP, Facebook Messenger, Slack, Telegram, and more._chatbotsmagazine.com Chatbots Magazine _Edit description_tinyletter.com Locutius - Letters on Conversational Interfaces by Abi Jones _The O'Reilly Bots Podcast covers advances in conversational user interfaces, artificial intelligence, and messaging…_www.oreilly.com O'Reilly Bots Podcast ideas and resources. — curated by the team Messaging Weekly Smooch — Curated by and the team Chatbots Weekly Omar Pera Reply.ai 🍜 Startups 🗣 Platforms _Actions on Google lets developers build experiences for the Google Assistant._developers.google.com Actions on Google | Actions on Google | Google Developers _Find companies with expertise in designing, developing and optimizing Alexa skills, from agencies and development to…_developer.amazon.com Find Experienced Skill Builders and Tools _I'm open-source, which means you can grab my smarts and put it in a device of your own design. Voice enable your fridge…_mycroft.ai Home - Mycroft _Cortana is your personal assistant, always ready to help you in every situation. See what the world's most personal…_www.microsoft.com Cortana - Meet your personal assistant - Microsoft - Global _Siri on Apple iPhone, iPad and iPod touch lets you use your voice to send messages, make calls, set reminders and more._www.apple.com iOS - Siri - Apple (UK) _Viv is an artificial intelligence platform that enables developers to create an intelligent, conversational interface…_viv.ai Viv 👔 Companies Capito Systems Cognitive Code — Silvia Mindmeld Nuance Verbio ( ) Raven Tech Acq by Baidu Mobvoi ☁️ Cloud Services Amazon Lex Amazon Polly Google Cloud Platform Microsoft Cognitive Services 🛠 Build - SDKs & Frameworks Assist Alexa Skills Kit Pullstring Conversable Bespoken Tools Api.ai for Google Assistant Api.ai for Amazon Alexa Kitt.ai Sayspring Houndify Smartly.ai Gomix IFTTT Mosaic - Extras This post by is a great place to get started: Brian Donohue _Last night betaworks and Amazon hosted the first NYC Amazon Alexa Meetup to bring Alexa owners and enthusiasts together…_medium.com Build your First Alexa Skill AlexaTutorial How to Build your First Amazon Alexa Skill (eBook) by Rocket Insights _Build your first custom skill in just 10 minutes (no programming experience required)._iot-for-all.com Alexa, What’s for Lunch? _At StdLib (“Standard Library”) we allow developers to deploy functions written in Node.js as infinitely scalable API…_hackernoon.com Build an Alexa Skill in 7 Minutes Flat with Node.js and StdLib _Simple builder for Alexa replies._www.npmjs.com alexa-message-builder 💼 Agencies Xandra Assist Rain Mobiquity Matchbox Solstice SciFutures VaynerMedia Witlingo, Inc. AKQA Razorfish Giant Spoon Iconmobile Newscycle Solutions Blink Mindshare TribalScale Volara Vectorform XAPPmedia, Inc. Unified Computer Intelligence Corporation UI Centric Opearlo VocaliD Conversant Labs Future of Voice 📈 Analytics VoiceLabs.co Opearlo Analytics Witlingo, Inc dashbot Botanalytics 🎙 Products Alexa Skills Store App on and iOS Android Unofficial Alexa Skills Store — list of commands that you can ask Google’s voice assistant OK Google Finie 🤖 Hardware Nucleus Jam Voice Ivee Jibo Whyd Kuri Lynx Hello Egg Triby IO Petnet TrackR Musaic Scout Alarm Garageio Toymail ecobee Luma ring Thalmic Labs embodied Owlet Vesper 🤑 Fundraising Alexa Fund Alexa Accelerator, powered by Techstars Lightspeed Ventures Launch Capital NextView Ventures — Betaworks Get Support from the Alexa Team at Betaworks’ Voicecamp _voicecamp is a program for anyone building within the ecosystem of conversational interfaces._betaworks.com voicecamp 💵 Alexa Fund (All the companies announced) Sutro invoxia Petnet Rachio mojio TrackR Musaic Scout Alarm Garageio Toymail Dragon Innovation Kitt.ai ecobee Luma ring Nucleus Defined Crowd Vesper 👥 People & Posts — General Partner . M.G. Siegler GV On Twitter _Vocal computing has a shot at being the next platform — or more — if the big guys don’t screw it up_500ish.com The Voice _“Voice will never be the interaction model,” they say, out loud, to communicate their thoughts._500ish.com Computing in Concert - partner at + runs . Matt Hartman betaworks Hearing Voices Newsletter On Twitter _The rise of services that live in Chatbots, Voice Computing, & Mixed Reality_render.betaworks.com Interfaces On Demand — people-first investor . Sarah Guo Greylock Partners On Twitter _Part 3 in a series on the Conversational Economy_news.greylock.com The Conversational Economy — Voice and the New Era of Multi-Modal Computing — Reporter at TechCrunch. Sarah Perez On Twitter _The next mainstream computing platform may not be bots, AR, or VR, but rather voice-based computing. According to a new…_techcrunch.com 24.5M voice-first devices expected to ship this year, but apps struggle to retain users — vp at . Patrick Montague betaworks On Twitter _Following the success of 2016’s botcamp, betaworks is pleased to announce camps as an ongoing product line. Each year…_render.betaworks.com Announcing Voicecamp — Freelance writer + developer. Owen Williams On Twitter _For decades the technology industry has been chasing the holy grail of computing: natural language conversation. Humans…_medium.com Google Home changed the way I think about voice assistants — CEO Assist. Shane Mac On Twitter _We are excited to announce that the Assist platform is powering one of the first brands on Google Home, Lonely Planet._medium.com Talk to Lonely Planet on Google Home — Senior Product Manager, Intercom. Hugh Durkin On Twitter _When consumer internet arrived in the 1990s, it ushered in a new age of communication. Free internet chat applications…_blog.intercom.com Why voice will be the dominant chatbot interface - Inside Intercom — Partner, . Aaron Batalion Lightspeed On Twitter _When I was a kid, my computer had a SoundBlaster card. If you were a geek like me, you remember editing your autoexec…_medium.com Skate to where the voice is going… — UX / product design . Johna Paolino General Assembly On Twitter _Two Simple User Experience Design Gestures that Delighted a Female User_medium.com Google Home vs Alexa — Trying to build a better company, every day and . Adam Marchick @VoiceLabsCo Kahuna — Co-Founder / EIR @ The Chernin Group. Alexandre Linares @VoiceLabsCo On Twitter _The Voice Report starts with the underlying hardware devices and works its way up the voice-first stack_read.acloud.guru The 2017 Voice Report — CEO and CoFounder, PullString. Prev, Pixar. Oren Jacob On Twitter — Founder + Editor at . Brian Roemmele Multiplex On Twitter _During the early computer era of the 1960s, it was thought there would only be the need for a few dozen computers. By…_techpinions.com There is A Revolution Ahead and It Has A Voice _“Apple buys smaller technology companies from time to time, and we generally do not discuss our purpose or plans”–Apple…_medium.com Apple’s Secret AI Technology: Meet Vocal IQ the self learning technology that is a part of Siri2. — Invented the hashtag; X Uber; Xoogler. Chris Messina On Twitter — Director of User Experience . Author of the O’Reilly book Designing Voice User Interfaces. Cathy Pearl @Sense_ly On Twitter _Edit description_www.amazon.com Designing Voice User Interfaces: Principles of Conversational Experiences — Strategically-oriented product design leader . Trip ODell @Amazon On Twitter _Several times a week, my children host an evening dance party in the living room. The playlist features all the modern…_medium.com Velveteen Rabbits: What a Children’s Story Can Teach Us About Computers that Talk. — Co-founder & Partner at NextView Ventures. David Beisel On Twitter _In the three months since I penned my initial blog post on "Ubiquity of Voice and the Venture Opportunity," I've been…_genuinevc.co Charting the Personal Voice Computing Startup Roadmap - GenuineVC Nithya Thadani — CEO of Rain _Last October, New York-based digital agency Rain worked with Campbell's to find a new way to push out the CPG giant's…_www.adweek.com How This Agency Built Its Own App Using Amazon Echo —I’m an Innovation-Obsessed Founder at Mylestone. Dave Balter On Twitter _Why Voice Assistants may be the answer you’ve been looking for._medium.com “Alexa, How Can I Get Unfair Ecosystem Advantage” — Partner at Lightspeed Venture Partners. Jeremy Liew On Twitter _Games have been a killer app for just about every new platform, from PCs to TVs (via game consoles) to Facebook to…_medium.com Games for Alexa — Co-Founder/CEO Siri & Viv Labs. Dag Kittlaus On Twitter _Why Viv is Joining Forces with Samsung_elevate.samsungnext.com The Path to Intelligence Everywhere — Co-founder of . Jan König HashtagNow On Twitter _Thoughts on Designing Seamless Voice Experiences_medium.com Alexa, Please Send This To My Screen 🚀 - A community helping facilitate connections to; I am working on an experiment - Get a skill made/make skills for people/companies- Find investors active in the field- Intros to other active enthusiasts- Bounce ideas around with others- Advice & mentorship from experienced individuals- Resources and tools to help you build- Discover interesting products and companies 👍 Please tap “♥︎” if you found this useful to help others see it too 👾 This post is also on GitHub and open for suggestions, just submit a pull request 👉 Feel free to follow and reach out on Twitter 🙏 Thanks to everyone who looked at this draft very early on! And perhaps I’ll see you all in the newsletter or 😉 Build Voices Side Note: I have ‘borrowed’ this template from which is an awesome post & newsletter I use to learn about Machine Learning. Thanks The Non-Technical Guide to Machine Learning & Artificial Intelligence Sam DeBrule 🙌

Ultimate Guide to Voice Assistants

Unsupervised Investments (I): A Guide to AI Investors

Arte Merritt, Co-Founder & CEO at will be presenting at the in San Francisco, 26–27 January and will explain how analytics in chatbots will differ from traditional web and mobile analytics, as well as how to use analytics to increase engagement, acquisition, and monetisation. Additionally, Arte will share the insights and learnings from the data Dashbot.io is capturing. Dashbot.io Virtual Assistant Summit I caught up with Arte ahead of the summit to discover what has driven his work with virtual assistants, what he thinks are the main factors enabling recent advancements, as well as his predictions for conversational agents in the next 5 years. What do you feel are the leading factors enabling recent advancements and uptake of virtual assistants? Conversational UI/UX is the future of human computer interaction. The Amazon Alexa is a great example of this. My co-founder often tells this story of how we used to see the videos of two year olds swiping on iPhones and iPads, now with his two young kids they’re talking to Alexa — “Alexa play the happy song… Alexa play Star Wars…” Jesse All the major players are opening up their platforms — Facebook opened up messenger, Apple opened iMessage, Microsoft opened Skype, Amazon opened Alexa, and Google is building an Alexa competitor. The brands are right there along side them building bots on these platforms. The users are already there as well — Facebook has nearly 1 billion users on Messenger. What do you feel is essential to future progress? Discovery. In the case of Facebook in particular, it’s hard to find bots or know what already exists. Anecdotally, I have a demo bot on both Facebook and Kik. In the case of Facebook, it only had ~30 users after nearly two months, whereas on Kik, it had nearly 15,000 users after two weeks — Kik has a bot store, Facebook doesn’t. In the cases where NLP is used, that needs to improve over time as well — or how bots handle the “I don’t know” responses. Paths to monetization are important as well. In the case of conversational chatbots, being able to complete a transaction entirely through the bot is important. What developments can we expect to see in virtual assistants in the next 5 years? With conversational interfaces, in the short term, we should see the major platforms launching bot stores, if they don’t already have one, adding monetization capabilities, and providing multi-user bot interactions, if they don’t already. The multi-user bot interaction is particularly useful — if you’re communicating with friends or co-workers in a messenger platform, it’s a lot more useful if you can pull the bot into the conversation, rather than have to bounce out. Imagine searching for a restaurant — instead of bouncing out to Yelp, you can bring Yelp into the conversation. The AI / NLP will get better overtime as well — making the conversations more natural, with better response rates and understanding of the actual intent. We’ll most likely see more interoperating amongst bots as well — having bots interact with other bots. What is your main goal at Dashbot.io? Dashbot.io is a bot analytics platform that enables enterprises and developers to increase user engagement, acquisition, and monetisation. In addition to standard metrics like engagement and retention, we have bot specific metrics like conversational analytics, sentiment analysis, and the full chat session transcripts. We also provide tools to take action on the data — like our live person take over of sessions to help lead a user to conversion and increase engagement. What has driven you to work on virtual assistants? We’re super excited about this space as the conversational data is much richer and more actionable than traditional web and mobile analytics. We can do some pretty interesting things based on the data — like insert a live person into a chat sessions to improve engagement and lead to conversion, re-engagement notifications, AI testing, and more. To hear from Arte and other experts in the field of virtual assistants, register now . Places are limited! Confirmed speakers include: Alonso Martinez, Technical Director at Pixar Animation Studios Lionel Cordesses, Innovation Project Manager at Renault (Elena) Corina Grigore, PhD Candidate at Yale University, Social Robotics Lab Amir Shevat, Director of Develop Relations at Slack Rick Collins, President of Enterprise at Next IT Dennis Mortensen, CEO & Founder at x.ai Anjuli Kannan, Software Engineer at Google The Virtual Assistant Summit will be running alongside the Deep Learning Summit , meaning attendees can enjoy additional sessions and networking opportunities. The European edition of the Virtual Assistant Summit will be taking place in London on 21–22 September! View the event here .

Got Data? Build a Better Bot with Analytics

hosted a night last night at in San Francisco. We bot demo WSGR It was great opportunity to see what people are doing with bots, across different platforms. The night featured bots for travel, food discovery, team building, entertainment, and even ones for finding a date or finding a contractor… not the same bot! :) Dashbot Our co-founder, Dennis, kicked off the night with an overview of ’s analytics platform. Dashbot If you’re building a bot, check it out — . It’s a great way to learn more about your bot and increase user engagement and retention. We recently added additional metrics around retention and messaging statistics. We also launched live person injection which enables you to insert messages into the session stream as if you’re the bot. We continually add new features, so feel free to provide feedback and suggestions. www.dashbot.io Demos The bot demo line up included: Alterra.ai Denis from Alterra demo’d how a user can discover new places to travel to as well as book hotels, all through natural conversation. “I’d like a warmer place, please…” Blackjack / ChatbotCity Rhett, recently developed a blackjack game inside Messenger. It’s built on top of his platform, ChatbotCity. Games are an interesting area with bots. It will be interesting to see what developers and publishers come up with in terms of conversational games. Much like with mobile apps, how developers made use of gestures and even the microphone to make interesting games, there are probably some cool ideas that can be done in conversation. We could all keep playing too. Zork Bubby Stephanie from Bubby demo’d their Matchmaking SMS bot. Dating and relationships seem like interesting areas for bots. Chris Messina Bot Ethan, Esther, and Chris demoed the Messina bot — a bot that enables people to schedule appointments with Chris, ask for Product Hunt help, and get additional news from Chris. This is an interesting area for bots — personal bots to offload some common requests and tasks. We’ve seen others with own bot as well as the bot — there’s even a bot. Esther’s Sarah cat Foxsy Yoyo demo’d the Foxsy bot — a tinder like dating bot. Growbot Justin demo’d growbot — a team feedback bot. Not only is it a way to provide quick praise for a teammate, but you can start to learn more about the company’s culture through the bot usage. Interestingly they originally had functionality for not so positive feedback, but as Justin described, the workplace isn’t quite ready for that… Jessie Humani / PullString Scott from Pullstring demoed Jessie Humani — this is a great example of an entertainment bot. Users can interact with Jessie, a young lady with a lot decisions to make. Having tried it, one of the nice things is the interaction keeps flowing along fairly seamlessly even when your responses might not completely match the conversation. You don’t get the “I don’t know” type responses from Jessie. Pullstring is also the creator of the Call of Duty bot which had over 6M messages in 24 hours. Tara.ai Syed demo’d Tara.ai’s bot for outsourcing projects, like having a mobile app built. The bot asks for the details of the project in a conversational manner and then either provides a quote for the project, if the AI recognizes the specs match similar past projects, or directs you to a project manager to complete the process. Tasteful Ravi demo’d Tasteful, a multi-platform bot for finding local restaurants. Bot Directory Our site lists many of the Facebook and Slack bots available and we have a Facebook Bot directory which enables you to discover, search for, and rate Messenger bots — it’s available at http://m.me/dashbot.io Until next time… The “Bot Space” has a vibrant community growing around it. We had a full house of attendees, many who stayed well past the official end to continue talking about bots. Stay tuned for our next event!

Bot Demo Night

How to Create a Dashboard to Track Your Twitter/X Follower Stats With APIs and GitHub Actions

এপিআই এবং গিটহাব অ্যাকশনগুলির সাথে আপনার টুইটার/এক্স ফলোয়ার পরিসংখ্যান ট্র্যাক করতে কীভাবে একটি ড্যাশবোর্ড তৈরি করবেন

So erstellen Sie ein Dashboard zum Verfolgen Ihrer Twitter/X-Follower-Statistiken mit APIs und GitHub-Aktionen

Cómo crear un panel para realizar un seguimiento de las estadísticas de sus seguidores de Twitter/X con API y acciones de GitHub

Comment créer un tableau de bord pour suivre les statistiques de vos abonnés Twitter/X avec des API et des actions GitHub

API और GitHub क्रियाओं के साथ अपने Twitter/X फ़ॉलोअर के आँकड़ों को ट्रैक करने के लिए डैशबोर्ड कैसे बनाएँ

API と GitHub Actions を使用して Twitter/X フォロワーの統計を追跡するダッシュボードを作成する方法

API 및 GitHub 작업을 사용하여 Twitter/X 팔로어 통계를 추적하는 대시보드를 만드는 방법

Como criar um painel para rastrear estatísticas de seguidores do Twitter/X com APIs e ações do GitHub

Как создать панель мониторинга для отслеживания статистики ваших подписчиков в Twitter/X с помощью API и действий GitHub

API'ler ve GitHub Eylemleriyle Twitter/X Takipçi İstatistiklerinizi Takip Etmek için Kontrol Paneli Nasıl Oluşturulur

Cách tạo Trang tổng quan để theo dõi số liệu thống kê về người theo dõi trên Twitter/X của bạn bằng API và hành động GitHub

如何使用 API 和 GitHub Actions 创建仪表板来跟踪您的 Twitter/X 关注者统计信息

Efficient Kubernetes Resource Management Across Multiple Clusters Using Modern Dashboards

Kubernetes Dashboard is a web-based user interface for performing Kubernetes operations. It helps to get a brief overview of workloads running in the cluster. With a Kubernetes dashboard, one can visualize Kubernetes(K8s) applications, monitor the performance, manage the cluster resources, and enable team collaboration between Developers and DevOps teams. As per the state of Kubernetes 2022 report by Vmware, the increase in the adoption of Kubernetes brings domain complexities into the process. In this blog, we will talk about the need for a Kubernetes dashboard,
the features provided by Devtron’s Kubernetes dashboard, and
how it can help you in Kubernetes management. Why is there a need for a Kubernetes dashboard? Kubernetes comes with a command line utility called “kubectl”. It is efficient enough to perform routine activities like deploying, updating, deleting, monitoring, and debugging within a cluster and on Kubernetes objects. Developers have to expend additional time and resources to learn an extra set of commands to debug in case of an issue in their application. It also becomes challenging to monitor and observe resources when dealing with Kubernetes at scale, especially in multi-cluster deployments. To solve all these challenges and accelerate software development, Kubernetes Dashboard was born. It provides a graphical user interface to manage your Kubernetes applications and clusters, making it really easy for developers to use. The K8s dashboard improves collaboration between the DevOps and developers by providing resource visibility and control, thus increasing productivity. Why the standard Kubernetes dashboard falls short of expectations? The vanilla Kubernetes dashboard provides essential features suitable for small-scale use cases. Though the community heavily uses it, it still has few challenges that we have listed down which you might face with the standard dashboard by Kubernetes. Unsupported multi-cluster and multi-cloud view: The standard Kubernetes Dashboard doesn’t support a multi-cluster view because it is designed with namespace first. This increases complexity at scale.
Manual RBAC: Kubernetes dashboards have RBAC that needs to be managed manually using a token or the kubeconfig file. In the case of Devtron, it has centralized access management wherein users don’t have to deal with RBAC or Kubeconfig files.
No SSO: The traditional Kubernetes dashboard doesn’t support SSO Login services, whereas it is a standard feature in Devtron’s Kubernetes Dashboard.
Complex node management: Users have to edit the entire Node manifest to make any changes, which is error-prone and cumbersome. With Devtron, one can efficiently perform node operations such as adding a taint, cordoning a node, etc., from the dashboard. However, Devtron also allows to access and edit the Node manifest for cases requiring advanced customization.
Absent cluster terminal access: In the traditional Kubernetes dashboard, users cannot use CLI tools like Netshot, Busybox, K9s, etc., for debugging clusters if required. Kubernetes dashboard by Devtron comes with cluster terminal access that helps users easily debug and troubleshoot cluster issues.
Unsupported Helm release management & resource grouping: The vanilla Kubernetes dashboard doesn’t provide any features to simplify the Helm release lifecycle but Devtron’s K8s dashboard supports Helm release management and provides an efficient way to deploy and observe helm charts. Presenting the Kubernetes Dashboard by Devtron The Kubernetes dashboard offered by Devtron is open-source and has multiple features that are not available in the standard dashboard on Kubernetes. From providing a comprehensive overview of Kubernetes resources deployed across multiple clusters to an intuitive user interface that enables development and operations teams to interact with Kubernetes clusters and collaborate, Devtron’s Kubernetes dashboard helps accelerate an organization’s maturity of operation on Kubernetes. The Kubernetes dashboard by Devtron comes with a wide range of features such as — helm release management, cluster terminal access, node operations from the dashboard, Kubernetes resource browser, cluster operations, and a lot more to manage your clusters and k8s applications. Let’s dive deep into the features that Devtron has to offer. K8s Clusters Management Kubernetes dashboard by Devtron provides a brief overview of clusters added to the dashboard and helps you monitor the cluster performance. It gives the real-time node health status and summary of nodes, including resource usages, labels, annotations, taints, pods on each node, and a lot more. The dashboard also helps you perform node operations such as: cordon a node,
drain a node,
taint a node,
debug node/cluster using cluster access terminal,
edit the node manifest,
delete a node from the Kubernetes dashboard. K8s Application Management The Kubernetes dashboard by Devtron comes with a dedicated K8s Resource Browser which provides a detailed overview of all k8s resources deployed in a cluster. The resource browser aggregates all k8s resources within a cluster and helps you quickly troubleshoot & debug from the intuitive dashboard. With the k8s resource browser, you can easily navigate across multiple clusters and filter resources by using the namespace filter, as highlighted in the image. It also allows you to create new resources through the K8s manifest. The resource browser helps you perform pod operations such as: check live manifest, edit & apply manifest changes,
check events,
view real-time logs,
exec into a terminal, and
delete resources and all that from the browser window. Helm Release Management The Kubernetes dashboard by Devtron is packaged with Helm Release Management and helps you deploy any helm chart directly to your cluster from the dashboard. It provides easy access to manage the entire lifecycle of a helm release. Though Helm is great at packaging K8s applications, it needs some catch-up regarding debugging and troubleshooting applications using Helm CLI. Helm CLI poses multiple challenges while managing the lifecycle of helm apps, like the absence of real-time monitoring, the inability to group resources, and no way to compare deployment values across multi-cluster deployments and a lot more. But the Devtron Kubernetes dashboard has addressed the complexities and challenges of Helm CLI. The dashboard provides a brief overview of helm apps deployed across multiple clusters and is rich in features such as: real-time application status,
grep logs across multiple pods with Log Analyzer,
k8s resource grouping at the application level,
check real-time logs of pods, check events, manifests,
exec into pod shell for easier debugging,
check configuration diff of helm charts deployed,
easy rollback with config details of each helm chart revision,
easily deploy and upgrade helm charts and a lot more. Conclusion The Kubernetes dashboard by Devtron is a holistic tool for Kubernetes management that takes care of all aspects of managing Kubernetes through a dashboard. We would love to hear your thoughts on the dashboard. Feel free to join the devtron discord community and give it a star if it helped ease your journey into Kubernetes or improved your day-to-day operations. Kubernetes Dashboard is a web-based user interface for performing Kubernetes operations. It helps to get a brief overview of workloads running in the cluster. With a Kubernetes dashboard, one can visualize Kubernetes(K8s) applications, monitor the performance, manage the cluster resources, and enable team collaboration between Developers and DevOps teams. As per the state of Kubernetes 2022 report by Vmware , the increase in the adoption of Kubernetes brings domain complexities into the process. state of Kubernetes 2022 report by Vmware state of Kubernetes 2022 report by Vmware In this blog, we will talk about the need for a Kubernetes dashboard, the features provided by Devtron’s Kubernetes dashboard, and how it can help you in Kubernetes management. the need for a Kubernetes dashboard, the features provided by Devtron’s Kubernetes dashboard, and how it can help you in Kubernetes management. Why is there a need for a Kubernetes dashboard? Kubernetes comes with a command line utility called “kubectl”. It is efficient enough to perform routine activities like deploying, updating, deleting, monitoring, and debugging within a cluster and on Kubernetes objects. Developers have to expend additional time and resources to learn an extra set of commands to debug in case of an issue in their application. It also becomes challenging to monitor and observe resources when dealing with Kubernetes at scale, especially in multi-cluster deployments. To solve all these challenges and accelerate software development, Kubernetes Dashboard was born. It provides a graphical user interface to manage your Kubernetes applications and clusters, making it really easy for developers to use. The K8s dashboard improves collaboration between the DevOps and developers by providing resource visibility and control, thus increasing productivity. Why the standard Kubernetes dashboard falls short of expectations? The vanilla Kubernetes dashboard provides essential features suitable for small-scale use cases. Though the community heavily uses it, it still has few challenges that we have listed down which you might face with the standard dashboard by Kubernetes. Unsupported multi-cluster and multi-cloud view: The standard Kubernetes Dashboard doesn’t support a multi-cluster view because it is designed with namespace first. This increases complexity at scale. Manual RBAC: Kubernetes dashboards have RBAC that needs to be managed manually using a token or the kubeconfig file. In the case of Devtron, it has centralized access management wherein users don’t have to deal with RBAC or Kubeconfig files. No SSO: The traditional Kubernetes dashboard doesn’t support SSO Login services, whereas it is a standard feature in Devtron’s Kubernetes Dashboard. Complex node management: Users have to edit the entire Node manifest to make any changes, which is error-prone and cumbersome. With Devtron, one can efficiently perform node operations such as adding a taint, cordoning a node, etc., from the dashboard. However, Devtron also allows to access and edit the Node manifest for cases requiring advanced customization. Absent cluster terminal access: In the traditional Kubernetes dashboard, users cannot use CLI tools like Netshot, Busybox, K9s, etc., for debugging clusters if required. Kubernetes dashboard by Devtron comes with cluster terminal access that helps users easily debug and troubleshoot cluster issues. Unsupported Helm release management & resource grouping: The vanilla Kubernetes dashboard doesn’t provide any features to simplify the Helm release lifecycle but Devtron’s K8s dashboard supports Helm release management and provides an efficient way to deploy and observe helm charts. Unsupported multi-cluster and multi-cloud view: The standard Kubernetes Dashboard doesn’t support a multi-cluster view because it is designed with namespace first. This increases complexity at scale. Manual RBAC: Kubernetes dashboards have RBAC that needs to be managed manually using a token or the kubeconfig file. In the case of Devtron, it has centralized access management wherein users don’t have to deal with RBAC or Kubeconfig files. No SSO: The traditional Kubernetes dashboard doesn’t support SSO Login services, whereas it is a standard feature in Devtron’s Kubernetes Dashboard. Complex node management: Users have to edit the entire Node manifest to make any changes, which is error-prone and cumbersome. With Devtron, one can efficiently perform node operations such as adding a taint, cordoning a node, etc., from the dashboard. However, Devtron also allows to access and edit the Node manifest for cases requiring advanced customization. Absent cluster terminal access: In the traditional Kubernetes dashboard, users cannot use CLI tools like Netshot, Busybox, K9s, etc., for debugging clusters if required. Kubernetes dashboard by Devtron comes with cluster terminal access that helps users easily debug and troubleshoot cluster issues. cluster terminal access cluster terminal access Unsupported Helm release management & resource grouping: The vanilla Kubernetes dashboard doesn’t provide any features to simplify the Helm release lifecycle but Devtron’s K8s dashboard supports Helm release management and provides an efficient way to deploy and observe helm charts. Presenting the Kubernetes Dashboard by Devtron The Kubernetes dashboard offered by Devtron is open-source and has multiple features that are not available in the standard dashboard on Kubernetes. From providing a comprehensive overview of Kubernetes resources deployed across multiple clusters to an intuitive user interface that enables development and operations teams to interact with Kubernetes clusters and collaborate, Devtron’s Kubernetes dashboard helps accelerate an organization’s maturity of operation on Kubernetes. The Kubernetes dashboard by Devtron comes with a wide range of features such as — helm release management, cluster terminal access, node operations from the dashboard, Kubernetes resource browser, cluster operations, and a lot more to manage your clusters and k8s applications. Let’s dive deep into the features that Devtron has to offer. K8s Clusters Management Kubernetes dashboard by Devtron provides a brief overview of clusters added to the dashboard and helps you monitor the cluster performance. It gives the real-time node health status and summary of nodes, including resource usages, labels, annotations, taints, pods on each node, and a lot more. The dashboard also helps you perform node operations such as: cordon a node, drain a node, taint a node, debug node/cluster using cluster access terminal, edit the node manifest, delete a node from the Kubernetes dashboard. cordon a node, drain a node, taint a node , taint a node taint a node debug node/cluster using cluster access terminal, edit the node manifest, delete a node from the Kubernetes dashboard. K8s Application Management The Kubernetes dashboard by Devtron comes with a dedicated K8s Resource Browser which provides a detailed overview of all k8s resources deployed in a cluster. The resource browser aggregates all k8s resources within a cluster and helps you quickly troubleshoot & debug from the intuitive dashboard. With the k8s resource browser, you can easily navigate across multiple clusters and filter resources by using the namespace filter, as highlighted in the image. It also allows you to create new resources through the K8s manifest. The resource browser helps you perform pod operations such as: check live manifest, edit & apply manifest changes, check events, view real-time logs, exec into a terminal, and delete resources and all that from the browser window. check live manifest, edit & apply manifest changes, check events, view real-time logs, exec into a terminal, and delete resources and all that from the browser window. Helm Release Management The Kubernetes dashboard by Devtron is packaged with Helm Release Management and helps you deploy any helm chart directly to your cluster from the dashboard. It provides easy access to manage the entire lifecycle of a helm release. Though Helm is great at packaging K8s applications, it needs some catch-up regarding debugging and troubleshooting applications using Helm CLI. Helm CLI poses multiple challenges while managing the lifecycle of helm apps, like the absence of real-time monitoring, the inability to group resources, and no way to compare deployment values across multi-cluster deployments and a lot more. But the Devtron Kubernetes dashboard has addressed the complexities and challenges of Helm CLI . complexities and challenges of Helm CLI complexities and challenges of Helm CLI The dashboard provides a brief overview of helm apps deployed across multiple clusters and is rich in features such as: real-time application status, grep logs across multiple pods with Log Analyzer, k8s resource grouping at the application level, check real-time logs of pods, check events, manifests, exec into pod shell for easier debugging, check configuration diff of helm charts deployed, easy rollback with config details of each helm chart revision, easily deploy and upgrade helm charts and a lot more. real-time application status, grep logs across multiple pods with Log Analyzer, k8s resource grouping at the application level, check real-time logs of pods, check events, manifests, exec into pod shell for easier debugging, check configuration diff of helm charts deployed, easy rollback with config details of each helm chart revision, easily deploy and upgrade helm charts and a lot more. Conclusion The Kubernetes dashboard by Devtron is a holistic tool for Kubernetes management that takes care of all aspects of managing Kubernetes through a dashboard. We would love to hear your thoughts on the dashboard. Feel free to join the devtron discord community and give it a star if it helped ease your journey into Kubernetes or improved your day-to-day operations. devtron discord community

How to Manage Kubernetes like a Pro with Kubernetes Dashboard by Devtron

Devtron দ্বারা Kubernetes ড্যাশবোর্ড সহ প্রো-এর মতো কুবারনেটস কীভাবে পরিচালনা করবেন

So verwalten Sie Kubernetes wie ein Profi mit dem Kubernetes Dashboard von Devtron

Cómo administrar Kubernetes como un profesional con Kubernetes Dashboard de Devtron

Comment gérer Kubernetes comme un pro avec Kubernetes Dashboard de Devtron

Devtron द्वारा Kubernetes डैशबोर्ड के साथ एक प्रो की तरह Kubernetes का प्रबंधन कैसे करें

Devtron の Kubernetes ダッシュボードを使用してプロのように Kubernetes を管理する方法

Devtron의 Kubernetes 대시보드를 사용하여 전문가처럼 Kubernetes를 관리하는 방법

Como gerenciar o Kubernetes como um profissional com o Kubernetes Dashboard da Devtron

Как управлять Kubernetes как профессионал с помощью Kubernetes Dashboard от Devtron

Kubernetes Dashboard by Devtron ile Kubernetes'i Profesyonel Gibi Yönetme

Cách quản lý Kubernetes như một chuyên gia với Bảng điều khiển Kubernetes của Devtron

如何使用 Devtron 的 Kubernetes 仪表板像专业人士一样管理 Kubernetes

Customizing Dashboards: Building a Custom Extensions Engine for Your Apps

In the world of web development, creating visually appealing and user-friendly dashboard interfaces is essential to leave a professional impression. To help developers enhance their skills and spark creativity, I've curated some of my favorite CodePen projects for various dashboard UIs. You will learn modern design techniques and efficient layout strategies that will elevate the aesthetics of your future projects. For each project, I will provide a direct link, an interactive preview, as well as the author links, so you can explore more of their work, too. Customer Management Dashboard By: Aysenur Turk https://codepen.io/TurkAysenur/pen/NWRqoyL?embedable=true Admin Dashboard By: Mert Cukuren https://codepen.io/knyttneve/pen/NWRWQeB?embedable=true Task Manager Dashboard By: Aysenur Turk https://codepen.io/TurkAysenur/pen/QWyPMgq?embedable=true Activities Dashboard By: Ecem Gokdogan https://codepen.io/ecemgo/pen/YzBZjjb?embedable=true Bank Dashboard By: Håvard Brynjulfsen https://codepen.io/havardob/pen/ExvwGBr?embedable=true Integrations Dashboard By: Håvard Brynjulfsen https://codepen.io/havardob/pen/jOwJWOG?embedable=true NFT Dashboard By: Dilum Sanjaya https://codepen.io/dilums/pen/YzrvrBy?embedable=true Digital Walls Dashboard By Max Böck https://codepen.io/mxbck/pen/ERNwBy?embedable=true Did You Like the Resources? Here's More 👇 Over the previous months, I've compiled The Ultimate Bundle with every resource you need from starting to learn to code to landing your dream tech role! Includes 900+ resources in total, further divided into 99 categories for easier navigation and access! Save 1000s of hours and focus on what matters! I'm currently offering 50% OFF just for my readers! Don't miss out on this! ⭐ Get it here: ! ⭐ Ultimate Resources Bundle to Land a Job in Tech Writing has always been my passion, and it gives me pleasure to help and inspire people. If you have any questions, feel free to reach out! Make sure to receive the best resources, tools, productivity tips, and career growth tips I discover by subscribing to ! my newsletter Also, connect with me on , , and ! Twitter LinkedIn GitHub Also published here

How to Improve Your Design Skills: 8 UI/UX Dashboard Projects to Inspire You 😍🎨

In most cases, Tableau tasks are scheduled to run at designated times, however, there may be occasions where the flexibility is not sufficient. If you're looking for a more flexible way to work with Tableau, you might want to check out the Tableau Server Client. It’s a Python library for the Tableau Server REST API. Using the TSC library, you can manage and change many of the Tableau Server and Tableau Cloud resources programmatically. Step 1: Authentication The provided Python code establishes a connection to Tableau Server using the Tableau Server Client (TSC) library. It authenticates using the provided account credentials and establishes a connection to the specified Tableau Server site. Once authenticated, the code allows access to Tableau Server resources for tasks such as querying data, publishing workbooks, and managing server content. import pandas as pd
import tableauserverclient as TSC

tableau_auth = TSC.TableauAuth('account', 'password', site_id='site_id')
server = TSC.Server('http://localhost', use_server_version=True)
server.auth.sign_in(tableau_auth) Make sure to replace ' ', ' ', and ' ' with actual credentials before running the code. account password site_id Step 2: List All Tasks and Find Task ID This code signs in to Tableau Server using provided authentication credentials, then retrieves all tasks from the server and creates a dataframe to store the , , and for each task. Taskid schedule_item task_type # get all tasks and find the Taskid
with server.auth.sign_in(tableau_auth):
    all_tasks, pagination_item = server.tasks.get()
    df_tasks = pd.DataFrame()
    df_tasks['Taskid'] = [task.id for task in all_tasks]
    df_tasks['schedule_item'] = [task.schedule_item for task in all_tasks]
    df_tasks['task_type'] = [task.task_type for task in all_tasks]
print(df_tasks) You can easily navigate through the dataframe to locate the specific task you wish to work with and then proceed to copy its corresponding Taskid in preparation for the next step. Step 3: Run or Delete a Task run a task You could use the following code to runs the specified extract refresh task, make sure to replace the with the actual id that you want to work with. id # replace the id 
with server.auth.sign_in(tableau_auth):
    task = server.tasks.get_by_id('9f9e9d9c-8b8a-8f8e-7d7c-7b7a6f6d6e6d')
    server.tasks.run(task)
    print("successfully refreshed") delete a task Deleting a task may not be as frequently utilized as running one, but it is just as straightforward. With the following code, you can smoothly delete a task. # delete a task
with server.auth.sign_in(tableau_auth):
    server.tasks.delete('9f9e9d9c-8b8a-8f8e-7d7c-7b7a6f6d6e6d')
    print("successfully deleted") References Tableau Server Client (Python) Tableau REST API Help Thank you for taking the time to explore data-related insights with me. I appreciate your engagement. If you find this information helpful, I invite you to follow me or connect with me on . Happy exploring!👋 LinkedIn

Using Python to Refresh Tableau Dashboard

These tools do more than just display data; they help in quickly reading, analyzing, and making informed decisions, which is critically important for both developers and businesses. A well-designed dashboard can become a key element in forecasting trends and anticipating outcomes, impacting the efficiency and motivation of the team. Hello! My name is Lisa, and I have worked as a product designer in large IT companies and small startups. Among my experience was the creation of internal products that help monitor metrics and the state of service operations. Thanks to this, I have accumulated significant experience in dashboard development, and today I want to share this experience with you. Today, I want to inspire you to create useful and effective dashboards by sharing my approach and emphasizing the importance of UI design in this process. The sense of dashboard I want to start with three fundamental principles that should guide the creation of dashboards. These are precisely what you, as a product manager or product designer, should advocate for: One of the less obvious but critically important tasks in dashboard creation is the ability . Visualization should not only display numbers but also convey context, show cause-and-effect relationships, and identify trends. This requires a deep understanding of how data correlates with real business processes and user behavior. Dashboard developers should aim not only to present data but also to explain it, creating an intuitive and engaging narrative structure. to tell a story with data Often in the dashboard development process, you may encounter the issue of “expectation overload” — when users want to see too many features and data. It’s important to be able to manage these expectations, explaining limitations and focusing on the most important aspects that truly add value. This might require communication and persuasion skills, as well as the ability to and the impact of various features on the final product. objectively assess priorities Technical and organizational obstacles often become a serious challenge. For instance, integrating data from various sources can be a complex task due to format incompatibilities or API limitations. In such cases, it’s crucial to to find solutions that ensure smooth integration and reliable system performance. It’s also important to consider organizational aspects, such as training the team to use the new dashboard and implementing it into work processes. closely collaborate with developers Goals Every successful dashboard begins with a clear understanding of its goals and audience. At my current job, before starting the development of a dashboard, we conduct . This could be, for example, monitoring key performance indicators for executives or providing technical data for the development team. an analysis of the objectives it needs to achieve and the audience it is intended for To illustrate, in one of our projects, the goal was to create a dashboard for monitoring server operations. The audience consisted of technical specialists who required detailed, real-time information about the system’s status. The goals and audience defined the structure and design of the dashboard, making it maximally informative and user-friendly for the end users. Moreover, an effective dashboard helps reduce risks for the company by providing For instance, thanks to the instant display of server downtime data, the team can quickly respond to issues, minimizing downtime and potential losses. quick access to critically important information. Equally important is the impact of the dashboard on the team’s motivation and awareness. When the team sees a dashboard tailored specifically for them with up-to-date metrics every day, it enhances their engagement and provides a clear understanding of the current state of the project. This creates a sense of control and confidence in the decisions being made, which in turn contributes to an overall increase in work efficiency. Users Before beginning the design of a dashboard, it’s critically important to understand . In my practice, this starts with a deep dive into the world of the end-users — developers, project managers, data analysts, and so on. I conduct interviews, analyze workflows, and gather feedback to understand their daily tasks and challenges. who the primary users will be and what tasks they will be addressing For example, might need real-time system performance monitoring, while may require an overview of task completion timelines and resources. By identifying these key usage scenarios, I can ensure that the dashboard will not only be functional but also maximally useful for specific users. developers project managers Next, I link the functionality of the dashboard to the overall It’s not just about presenting data; it’s about how these data can help achieve specific objectives. For instance, if a business goal is to increase efficiency, then the dashboard should highlight metrics that track progress and identify bottlenecks. business goals of the company. In one of the projects, the goal was to improve customer service quality. For this, we developed a dashboard that displayed key indicators in real-time related to the processing of customer inquiries, allowing the team to respond promptly to issues and improve service quality. Thus, understanding both user needs and business goals not only displays data but actively contributes to achieving the organization’s ultimate goals. Strategy When we start defining the key functions and priorities of a dashboard, it’s important to find a balance between what users want and what is truly needed to achieve business goals. In my experience, I begin by creating a list of features that could be useful and then prioritize them based on their impact on users and business objectives. For instance, for a dashboard designed for monitoring application performance, key features might include displaying system response time, code errors, and server load levels. This is not just about having “nice-to-have” features; it’s about creating a “must-have” list that is guided by strategic goals and the real needs of the user. In developing a dashboard, I always think about how it will fit into the broader context of the product. 👾How will it interact with other features? 📎 How will it help the user better understand and use the product as a whole? For example, if a dashboard is designed for a CRM system, it should not only provide data but also simplify interactions with customers and improve processes for working with them. In this way, we make the dashboard . a valuable addition, not just an isolated tool Design. Prototyping. Iterations. I start with basic sketches that allow for a quick assessment of ideas and structure. These sketches are more than just drawings; they help me and my team visualize the dashboard concept and initiate a dialogue about how it should function. Once the concept is approved, I move on to creating more detailed prototypes. I develop prototypes that not only resemble the final product but also . This is a critically important step as it allows for testing with real users and gathering feedback that will influence subsequent design iterations. give an insight into user interaction When designing the dashboard interface, my main goal is to create an intuitive and effective user experience. Here are a few key principles I always keep in mind: 🎧 Clarity and Noise Reduction It’s important that users can quickly understand what is displayed on the dashboard. I aim to avoid information overload, focusing on key metrics and data necessary for the specific audience. 🧭 Consistency and Predictability I use consistent design elements and layouts so that users can intuitively understand how to interact with the dashboard. This includes uniformity in colors, fonts, and layouts. 💠 Interactivity and Feedback The dashboard should be informative as well as interactive. I include elements such as filters and dropdown menus that allow users to customize data display according to their preferences. 🍟 Accessibility and User-Friendliness I believe that design should be accessible to all users. This includes considering people with different abilities and preferences, as well as ensuring that the dashboard is user-friendly on various devices. Data Visualization and Information Architecture One of the key aspects of creating effective dashboards is the proper selection of data . Each data type requires its own approach to presentation to ensure the information is understandable and easily digestible. visualization methods For example, line charts are ideal for time series as they clearly illustrate the dynamics of changes. Bar or pie charts work well for comparing values across categories. Heat maps can be useful in visualizing complex datasets, allowing for quick identification of patterns and anomalies. It’s important to remember that visualization should be not only informative but also . I use colors and shapes to make data more accessible and comprehensible, while avoiding overloading with visual information. appealing Additionally, I focus on and ensuring a consistent flow of information, which aids users in easily navigating and finding the data they need. For instance, in a dashboard designed for sales analysis, I might group data related to customer demographics, sales figures, and product performance in distinct but interconnected sections. This way, a sales manager can quickly locate specific insights, such as the best-selling products in a particular demographic segment. grouping related data Another example is a financial dashboard where I categorize data into revenue, expenses, and profit margins. By doing so, financial analysts can effortlessly switch between different financial aspects without losing track of the overall financial health of the company. These thoughtful groupings and layouts not only improve the usability of the dashboard but also enhance the decision-making process by presenting a coherent narrative of the data. Testing and Iteration To identify usability issues and understand how well the dashboard meets users’ needs and expectations, we showcase our developments to real users. Based on the feedback collected, the process of iterations begins. The key is to be the design in response to the data received. Iterations can affect both minor details of the interface and larger aspects of structure and functionality. open to changes and ready to adapt In one of our recent projects on creating a dashboard for server performance monitoring, user testing became a pivotal moment. After the initial development of the dashboard, we conducted a series of tests with our development team, who were the primary users of the product. During these sessions, I observed how they interacted with the dashboard, . A key issue was that the developers had trouble interpreting the performance time series. The charts were overloaded with data, making it difficult to quickly analyze the situation. noting any difficulties or misunderstandings Based on this initial testing, we began the process of iterative improvements. Our first step was to simplify the charts by highlighting the most critical metrics and reducing visual clutter. We also added the ability to filter data by time intervals, allowing developers to focus more easily on specific periods. After implementing these changes, we conducted , this time with a broader group of users, including project managers. The feedback was significantly more positive: the charts became clearer, and the data filtering feature was particularly appreciated for its usefulness. a second round of testing Product Integration The next key stage is the integration of the dashboard into the overall product. In my project of creating a dashboard for server monitoring, one of the main tasks was to ensure its . This required close collaboration with the development team to ensure that the dashboard accurately collects and displays data in real-time. seamless integration with the existing system We utilized APIs to connect the dashboard to various data sources, ensuring high performance and reliability. Work was also done to optimize data loading so that the dashboard could respond quickly to user queries, even when processing large volumes of information. It’s crucial that the dashboard not only meets current needs but can also . To this end, we developed a modular architecture that allows for the easy addition of new features and the integration of additional data sources. Ensuring continuous support and updates for the dashboard was also an important part of the process, guaranteeing its stability and the relevance of its data. adapt to future changes and expansions of the system Creating dashboards is an integral part of product design. They not only provide valuable information for decision-making but also significantly enhance user convenience and efficiency. My experience has shown that a well-designed dashboard can have a substantial impact on business, improving processes and aiding in the achievement of goals. Tips and Tricks for Product Designers Start by figuring out what your users and . It’s like being a detective, but instead of solving crimes, you’re solving design puzzles. business really need Regularly . Be ready to iterate based on the feedback test the dashboard with real users Aim for in data visualization. Avoid information overload and focus on the key metrics. simplicity Develop dashboards with and potential data or process changes in mind. future scaling Postscript Alternative Ways to Create Dashboards: No-Code and Low-Code Solutions In the modern world of product design, there is an increasing number of . These no-code and low-code platforms offer convenient means for quick and efficient dashboard development, making them accessible not just for professional developers but also for business analysts, marketers, and other specialists. tools that allow for dashboard creation without deep programming knowledge Platforms: is  a powerful platform for creating interactive dashboards, particularly valuable for monitoring and analyzing time-series data. Ideal for real-time system monitoring, network analysis, and IoT applications, Grafana supports multiple data sources, including Prometheus, MySQL, PostgreSQL, and many others. This tool is highly flexible in visualization customization, allowing for detailed and adjustable dashboards. However, it may require deeper technical knowledge for setup and use compared to other no-code/low-code solutions. Grafana is one of the most popular platforms for data visualization. It offers robust tools for creating a variety of dashboards with the ability to connect to different data sources. Tableau makes it easy to integrate data from various sources and create interactive dashboards. It is ideal for integration with other Microsoft products, such as Excel and Azure. Microsoft Power BI is a free solution from Google that allows for creating customizable dashboards. Particularly well-suited for working with data from Google Analytics, Google Ads, and other Google services. Google Data Studio : This tool provides flexible options for dashboard creation and business analytics. It enables not just data visualization but also in-depth analysis. Looker Using no-code and low-code platforms has its advantages, including . However, one should consider their limitations in terms of customization and integration with some complex systems. Therefore, it’s important to assess the needs of the project and choose a tool that best meets these requirements. development speed, ease of use, and flexibility in design alteration

Creating the Perfect Dashboard: Visualizing Your Metrics

নিখুঁত ড্যাশবোর্ড তৈরি করা: আপনার মেট্রিক্স ভিজ্যুয়ালাইজ করা

Erstellen des perfekten Dashboards: Visualisierung Ihrer Metriken

Creando el panel perfecto: visualizando tus métricas

Créer le tableau de bord parfait : visualiser vos métriques

परफेक्ट डैशबोर्ड बनाना: अपने मेट्रिक्स को विज़ुअलाइज़ करना

完璧なダッシュボードの作成: 指標の視覚化

완벽한 대시보드 만들기: 측정항목 시각화

Criando o painel perfeito: visualizando suas métricas

Создание идеальной информационной панели: визуализация показателей

Mükemmel Kontrol Panelini Oluşturma: Metriklerinizi Görselleştirme

Tạo Trang tổng quan hoàn hảo: Trực quan hóa các chỉ số của bạn

创建完美的仪表板：可视化您的指标

Why Do You Generally Need to Create a Date Table in Power BI, While It Is Not Necessary in Tableau? In Power BI, a date table is necessary because the DAX language does not support built-in date functions, requiring the creation of a date table to perform date-related analysis. In Tableau, no date table is needed as it supports built-in date functions and features for direct use of date fields in analysis. How to Create a Date Table in Power BI? To create a date table in Power BI using DAX, you can follow these steps: Open Power BI Desktop and go to the Modeling tab. Click on New Table in the Modeling tab to create a new table. In the formula bar, enter the DAX code to generate the date table. Here's an example of the DAX code to create a date table: Calendar = ADDCOLUMNS (
	CALENDAR (date(2021,1,1),date(2023,12,31)),
	"Year", YEAR ( [Date] ),
	"Quarter", ROUNDUP( MONTH ( [Date] )/3,0 ),
	"Month", MONTH ( [Date] ),
	"Week", WEEKNUM([Date]),
	"Year Quarter", YEAR ( [Date] ) & "Q" & ROUNDUP( MONTH ( [Date] )/3,0 ) ,
	"Year Month", YEAR ( [Date] ) * 100 + MONTH ( [Date] ),
	"Year Week", YEAR ( [Date] ) * 100 + WEEKNUM ( [Date] ),
	"Weekday", WEEKDAY([Date])
    ) This DAX code creates a calendar table with additional columns for year, quarter, month, week, year quarter, year month, year week, and weekday. Here's a breakdown of each part of the code: : This is the name of the new table being created. Calendar = : This function adds new columns to an existing table. ADDCOLUMNS ( ... ) : This function creates a table with a single column of dates, starting from January 1, 2021, to December 31, 2023. CALENDAR (date(2021,1,1),date(2023,12,31)) : This creates a new column named Year which extracts the year from the date in the Date column. Year, YEAR ( [Date] ) : This creates a new column named Quarter which calculates the quarter based on the month in the Date column. The ROUNDUP function rounds up the result to the nearest whole number. Quarter, ROUNDUP( MONTH ( [Date] )/3,0 ) : This creates a new column named Month which extracts the month from the date in the Date column. Month, MONTH ( [Date] ) : This creates a new column named Week which calculates the week number based on the date in the Date column. Week, WEEKNUM([Date]) : This creates a new column named Year Quarter which combines the year and quarter information. Year Quarter, YEAR ( [Date] ) & Q & ROUNDUP( MONTH ( [Date] )/3,0 ) : This creates a new column named Year Month which combines the year and month information into a single number. Year Month, YEAR ( [Date] ) * 100 + MONTH ( [Date] ) : This creates a new column named Year Week which combines the year and week information into a single number. Year Week, YEAR ( [Date] ) * 100 + WEEKNUM ( [Date] ) : This creates a new column named Weekday which calculates the day of the week (1 for Sunday, 2 for Monday, and so on) based on the date in the Date column. Weekday, WEEKDAY([Date]) In summary, this code creates a calendar table with additional columns to provide various ways of organizing and analyzing date-related data. Dynamic Date Table To create a dynamic date table for the most recent three years, you can use the following code. Calendar = ADDCOLUMNS (
	CALENDAR(DATE(YEAR(TODAY())-1,1,1),DATE(YEAR(TODAY())+1,12,31)),
	"Year", YEAR ( [Date] ),
	"Quarter", ROUNDUP( MONTH ( [Date] )/3,0 ),
	"Month", MONTH ( [Date] ),
	"Week", WEEKNUM([Date]),
	"Year Quarter", YEAR ( [Date] ) & "Q" & ROUNDUP( MONTH ( [Date] )/3,0 ) ,
	"Year Month", YEAR ( [Date] ) * 100 + MONTH ( [Date] ),
	"Year Week", YEAR ( [Date] ) * 100 + WEEKNUM ( [Date] ),
	"Weekday", WEEKDAY([Date])
    ) In the current DAX code, the date range is specified as one year ago to one year ahead using and . This determines the range of dates included in the dynamic date table. DATE(YEAR(TODAY())-1,1,1) DATE(YEAR(TODAY())+1,12,31) Thank you for taking the time to explore data-related insights with me. I appreciate your engagement. If you find this information helpful, I invite you to follow me or connect with me on . Happy exploring!👋 LinkedIn Also published here

How to Create a Dynamic Date Table in Power BI: An Essential Step for Dashboard Creation

In this guide, I'll demonstrate the surprisingly straightforward process of exporting charts from a Dashboard using a popular open-source JavaScript library and a few lines of code. I began by designing a basic dashboard featuring three types of charts: a line chart, a bar chart, and a pie chart. While I opted for ChartJS for this project, other libraries like D3 or ECharts are also viable choices. Each chart widget in the dashboard includes a header button, which initiates the export process. Here's a glimpse of the dashboard setup: The second phase involves setting up the export feature. For this, I selected jsPDF, a versatile open-source JavaScript library that facilitates the conversion of charts to PDF format. This library is compatible with any JavaScript framework, though my example uses plain JavaScript. We can integrate jsPDF into a project via CDN. The export functionality activates upon clicking the export button. The process is broken down into the following five steps: Identifying the chart element. Transforming it into an image. Initializing jsPDF with a chosen orientation. Incorporating the image into the PDF in PNG format with appropriate dimensions. Finalizing the PDF. The corresponding code snippet is as follows: window.jsPDF = window.jspdf.jsPDF;

const exportChart = (id, dimensions) => {
  const chartEl = document.getElementById(id);
  const image = chartEl.toDataURL('image/png', 1.0);

  const pdf = new jsPDF('landscape');
  pdf.addImage(image, 'PNG', ...dimensions);
  pdf.save('chart.pdf');
} To streamline the process, I encapsulated these steps into a single function, eliminating redundant code. This function requires just the element's id and its dimensions as inputs. You can find the complete dashboard implementation on my . GitHub page As evident, the implementation is concise, requiring just five lines of code. However, this example is quite basic. In a more complex scenario, we might need to add text, titles, pagination, etc. This can be achieved by consulting the jsPDF documentation. I hope this brief tutorial proves useful. The best way to understand it is by trying it out yourself. Happy coding!

Five Simple Steps to Convert Dashboard Charts Into PDFs

Hi! My name is Mava. Since 2017 I have been interested in exchanges, stocks, etc. At the beginning of 2019, I was completely overwhelmed by the wave of crypto hype. In this story, I will tell you how I created a crypto dashboard, which was born from the simple idea of ​​calculating profit. At first, I traded manually, then I used trading bots. One bot - I didn’t like the management. The other one was awkward to set up. The third was quite suitable, with its inconveniences, but I could live with it. The fourth one was the most successful! And it was cool: trade was going on, there was a profit! And only 99% remained until the Lambo (just kidding). I tried several bots and even used one of them until now, they all had the same problem: they did not show profit they did not show the average price of my assets. they did not have any statistics on my trading. The exchange can give you PNL or a list of your transactions in Excel and that’s it. And what should I do about it? What is my profit? How much is invested now? What is the value of the assets at market prices? Therefore, I made myself an Excel file into which I transferred the list of completed transactions. I wrote formulas so that based on these transactions, it was possible to calculate the profit for each coin. I also added a loading of coin prices to understand what the average cost of the coins I have is. It turned out to be a huge file that needed to be updated constantly. But it showed me the information I needed. I switched the bot from one coin to another because I saw that it did not bring profit. I realized how badly I was screwing up with another coin whose trading needed to be stopped. I could calculate the amount needed to average to break even. And all this time, in the bot support chat, I saw users asking the developers “How to calculate profit? How to calculate the average price? How can I average?”. The response was vague answers that made no sense. So I decided to "make my Excel file accessible to everyone" - I decided to create a service that would help people understand what was happening with their trading, what was happening with their assets, and what their options were. I gave up trading and devoted myself entirely to creating a service. My dear wife has created a name for this service - TotalProfit. It was the most suitable name that fully revealed the idea of the service! I found a programmer who is helping me create a service. The two of us have been doing this for quite a long time because I don’t have investors to hire several freelancers - I do everything with my funds. I came up with a logo that has already changed ten times and now this is exactly what I need, which does not bother me to this day. It's funny, but instead of finishing current work, I constantly come up with new features for the project. During the creation of the project, it acquired other auxiliary functions: from a simple calculation of profit, it turned into a large crypto dashboard, with a portfolio chart, profit charts, trading volume charts, calculators, a portfolio that shows the real value of assets with profit or losses, as well as averaging options, convenient viewing of trading history and so on. And now, I understand that I have reached the MVP level. But I need to go further - not all my ideas are brought to life in this project: I need to implement other exchanges (now only one for testing time), I need to check the performance of the service under load, and so on. In plans, we will add tax calculations according to different schemes: LIFO, FIFO, and average; futures trading analysis, notifications in telegrams about the price reaching a particular level and much more. I have too much at stake to stop! But I can already see that the project is alive, and working and has already started helping people!

From Crypto Trader to Dashboard Creator

Dashboard software has become a necessary tool for businesses. With all the information you must gather and monitor about your business, you may wonder how to get the most out of it. Actionable insight can help you gain a competitive edge, considering the gap between data and business value. In fact, in 2023, achieved measurable value from and analytics investments, which reinforces the need for data-driven decision-making. 91.9% of organizations data to ensure you understand your data and benefit from it. Dashboard software merges data from linked databases and provides a customizable and interactive platform for data visualization Additionally, it empowers everyone in your company, from a data analyst to a junior manager, allowing them to visualize, present, and use data in any way that makes sense to them. In this article, we’ll explore the most eminent benefits of dashboard software and how you can leverage them to get the most out of your investment. 1. Effective Data Visualization Businesses gather huge amounts of data. Understanding such amounts of data can be challenging and time-consuming, to say the least, necessitating the need for tools that can help organize your data in a manner you can comprehend. When this is not possible, your business may experience challenges in making decisions and executing them in time. How can you make decisions based on data communicated ineffectively? Similarly, . This leads to a lot of time wasted trying to organize and present huge amounts of data. without data visualization, your employees may not know where to focus their attention to improve productivity One of the benefits of dashboard software is its ability to transform your business data into easy-to-understand graphs, images, and charts, which are essential considering that the human brain processes visual information more readily than textual information. Actually, the use of visual language is proven to enhance effectiveness and efficiency, leading to 24% shorter meetings. It is safe to conclude that this statistic is only possible because visualization enables data to be easily communicated and understood. The software interprets and simplifies the data for you to help generate true value for your business. It becomes easier to make decisions, recognize patterns and errors, and improve data analysis. GenerationE is an IT solutions provider that captures and automates best practices for IT operations by up to 85%. InetSoft provided a visualization layer for GenerationE, helping the company and saving its team the effort of charting and analyzing log data in external reporting systems. monitor the performance of automated processes 2. Improves Decision Making Great data, when analyzed correctly, can help enhance decision-making. It is important to gather and analyze business data to understand key business metrics and your performance to help you make better decisions to upscale. Without good dashboard software, your business may experience challenges collecting and managing data as it is scattered across multiple databases. Even if you can access this data from siloed systems, moving and analyzing it manually takes time and can impede accurate reporting and fast decision-making. Slow and inefficient decision-making can negatively impact your business in 2024 by costing you missed opportunities, time, and money. Dashboard software merges data from different sources and provides immediate access to at-a-glance information, ensuring you make decisions quickly to avoid missing out on opportunities. Additionally, with clear, actionable insights, you can make more accurate data-driven decisions and create business-boosting strategies to give you a competitive edge. In fact, Insight-driven businesses are growing at an average of , according to a report by Forrester. 30% each year This figure summarizes the when it comes to decision-making. Data in the digital era is extremely critical, and it helps to have the right tools to help you leverage. benefits of dashboard software Kreditech is a financial company based in Germany that offers clients loans based on their creditworthiness. Data analysis and decision-making are therefore critical. After incorporating Datapine, Kreditech was able to decentralize decision-making and achieve faster and smarter data-driven decisions. Thanks to the software’s friendly interface, users were able to work with zero IT overhead. 3. Increases Business Efficiency Enhancing business efficiency can help grow your business. It is undeniable how critical business efficiency is to grow and survive in the current economic climate. Without dashboard software, your business risks inefficiencies due to siloed information, manual data entry processes, ineffective data organization, and presentation. To err is human, so inefficiencies can frequently occur without the right tools to streamline business intelligence operations. Manual processes can also lead to data errors that are more prevalent when dealing with large amounts of data. In fact, Gartner found out that organizations believe poor data quality to be responsible for per year in losses. an average of $15 million For starters, reducing manual tasks is a key component for successful business management and plays a huge role in increasing efficiencies. It is a no-brainer that automation technologies like dashboard software can achieve more than a human and deliver more efficient results through workflow automation. A dashboard software offers smart, autonomous data management solutions to help you save time and money by gathering quality insights. Additionally, dashboard software brings data from different sources into a central respiratory system, eliminating the need for multiple external solutions. Therefore, you can be able to take quick action on your data-driven insights to upscale your business. Parcero is a Columbian marketing agency that was looking for a solution to help save time on manual processes. After implementing Klipfolio, Parcero was able to automate client reporting and enhance efficiency. They recorded in repetitive advertising tasks and 73% in repetitive reporting tasks. 33% time savings 4. Empowers End-Users Dashboard software empowers your employees to be self-reliant. The amount of time wasted waiting for data analysts and IT teams to present and explain data is a lot. This is not to mention that it distracts them from focusing on their job to advance the business’s goals. Unfortunately, there remains a huge gap between having data and being able to use it. Even with huge amounts of data, most businesses need help to take action on the valuable insight because they cannot interpret it. In fact, struggle with utilizing their , according to Talend. 78% of executives data for decision-making Imagine how much you could achieve if your employees could access and interpret data on their own without relying on data analysts. Well, one of the in business intelligence is empowering end-users by providing a simplified and clear platform where they can access data and manipulate it in a way that makes sense to them. benefits of dashboard software This ensures enhanced productivity, prompt decision-making, and minimized costs thanks to the ability to get answers independently without needing help from the BI or IT team. This also allows your IT team to focus on their job without being distracted by frequent help requests. GMS is a leading distributor of construction products based in Georgia. The company was looking for an easy-to-implement solution to help users access valuable insights. Thanks to InetSoft, GMS users can based on data consolidated into interactive reports that are easy to read. make quick business decisions 5. Reduces Operating Costs Dashboard software can minimize business costs. Without a great dashboard software in 2024, data remains fragmented across multiple systems and databases, impeding prompt decision-making. Siloed data can result in expensive operational costs caused by inefficiencies, analysis, and manual data collection. . Without , your employees may spend hours fetching and trying to interpret data. Time is money, and when you are losing both, you could be laying a foundation for your business’s failure the right tools In fact, Airtable’s research revealed that knowledge workers reported spending nearly 29% of their week (11.6 hrs) searching for the key information they need to do their work. Conversely, implementing dashboard software provides a central repository that combines and organizes data from different sources to provide clear visibility of key metrics. . It also provides a unified view that lets you easily identify cost-saving optimization opportunities and budget allocation opportunities In addition to that, dashboard software capabilities such as automation help to eliminate manual and repetitive tasks that can be time-consuming. Consequently, this reduces the chances of inefficiencies and errors that could cost you money. Dashboard software significantly reduces operational expenses by identifying inefficiencies promptly, optimizing resource allocation, and making data-driven decisions, ultimately contributing to substantial cost savings. Just Spices is a German-based company that manufactures spices. The company had been investing a lot of time in extracting and analyzing data for a while. With Klipfolio, Just Spices as they could access and visualize key metrics that show different departments where help is needed instead of having people extract data. saved time and money Conclusion In the digital age, data is extremely essential for businesses. How you use the business data you gather can influence the success of your business. However, with vast amounts of data, it can be challenging even for experts to organize and leverage data to get the best out of it. Dashboard software benefits such as reduced costs, enhanced efficiency, and clear visibility into key metrics can set your business apart. Actually, according to Capgemini, say its company’s Big Data initiatives are profitable. 27% of business executives Investing in a great dashboard software in 2024 can empower small businesses with enterprise-level insight without exaggerated costs.

5 Benefits of Dashboard Software for Business Intelligence in 2024

In a data-intensive industry like finance, data comes from numerous entries and goes to numerous exits. Such status quo can easily, and almost inevitably, lead to chaos in data analysis and management. For example, analysts from different business lines define their own financial metrics in data reports. When you pool these countless reports together in your data architecture, you will find that many metrics overlap or even contradict each other in definition. The consequence is, developing a simple data report will require lots of clarification back and forth, making the process more complicated and time-consuming than it should be. As your business grows, your data management will arrive at a point when "standardization" is needed. In terms of data engineering, that means you need a data platform where you can produce and manage all metrics. That's your architectural prerequisite to provide efficient financial services. This article introduces the lifecycle of financial metrics in a database (in this case, ), from how they're produced to how they're efficiently presented in data reports. You will get an inside view of what's behind those fancy financial dashboards. Apache Doris Define New Metrics & Add Them to Your Database Fundamentally, metrics are fields in a table. To provide a more concrete idea of them, I will explain with an example in the banking industry. Banks measure the assets of customers by AUM (Assets Under Management). In this scenario, AUM is an , which is often a field in the source data table. On the basis of AUM, analysts derive a series of , such as "year-on-year AUM growth", "month-on-month AUM growth", and "AUM per customer". atomic metric derivative metrics Once you define the new metrics, you add them to your data reports, which involves a few simple configurations in Apache Doris: Developers update the metadata accordingly, register the base table where the metrics are derived, configure the data granularity and update frequency of intermediate tables, and input the metric name and definition. Some engineers will also monitor the metrics to identify abnormalities and remove redundant metrics based on a metric evaluation system. When the metrics are soundly put in place, you can ingest new data into your database to get your data reports. For example, if you ingest CSV files, we recommend the Stream Load method of Apache Doris and a file size of 1~10G per batch. Eventually, these metrics will be visualized in data charts. Calculate Your Metrics As is mentioned, some metrics are produced by combining multiple fields in the source table. In data engineering, that is a multi-table join query. Based on the optimization experience of an Apache Doris user, we recommend flat tables instead of Star/Snowflake Schema. The user reduced the query response time on tables of 100 million rows after such a change. from 5s to 63ms The flat table solution also eliminates jitter. Enable SQL Caching to Reduce Resource Consumption Analysts often check data reports of the same metrics on a regular basis. These reports are produced by the same SQL, so one way to further improve query speed is SQL caching. Here is how it turns out in a use case with SQL caching enabled. All queries are responded within 10ms; When computing 30 metrics simultaneously (over 120 SQL commands), results can be returned within 600ms; A TPS (Transactions Per Second) of 300 is reached, with CPU, memory, disk, and I/O usage under 80%; Under the recommended cluster size, over 10,000 metrics can be cached, which means you can save a lot of computation resources. Conclusion The complexity of data analysis in the financial industry lies in the data itself other than the engineering side. Thus, the underlying data architecture should focus on facilitating the unified and efficient management of data. Apache Doris provides the flexibility of simple metric registration and the ability of fast and resource-efficient metric computation. In this case, the user is able to handle 10,000 active financial metrics in 10,000 dashboards with 30% less ETL efforts.

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