What are cookies? Cookies are simply the created by the developers of a particular website, which are for storing the data for further recognition and preferences set by the user. They are also known as an HTTP cookie, web cookie, Internet cookie, browser cookie, or only a cookie. text files stored in the user’s computer They are widely used on almost every website you visit. Cookies can store the data, such as the language preferences set by users on their first visit, or the time when you last visited the website. Data could also include the links that you’ve clicked during the session. The type of data saved to a cookie is set lawfully by the developers of that website. Just like if you visit a website and log into your account, the cookie saves the information, and when you come back after some days later, it redirects you to the account you previously logged into. There are several types of cookies for distinct tasks - These are the cookies used and saved just during the session by the user. After the session, the cookies get deleted automatically by the browser. Session cookie - They are the cookies stored in the user’s device for a long time. They are used to remember information like settings, log-in, or sign-up credentials. Which therefore makes the user experience faster. Permanent cookies - Cookies regenerated automatically even after deletion by the user are known as zombie cookies. These are mainly used for counting the visitors in terms of unique or no-unique. Zombie cookie - They are used mainly for advertisements and video purposes and accessed by Adobe Flash. Flash cookie - They are used by different services irrespective of the website you visit. They use the cookie for tracking the details of visitors to a particular website. These are used in chatbots, newsletters, and for other purposes as well. Third-party cookies How Do Websites Use Cookies? For websites, cookies are majorly essential to every time. keep the user experience flawless The cookies in the browser or your device’s hardware store the data in the 'field-value' pairs; for example, yourName = “Prakshal”. It stores different values in different fields. This tells cookies what data is to be sent for a particular field. When you visit a website, your credentials’ data in the form of cookies are being sent to the browser for storing and future purposes. When you re-visit the website, . The website then uses the cookie data so that the changes you’ve made last time could easily be retrieved. This literally makes the user experience polished. your web browser returns that data to the particular website in the form of a cookie The Power Of Using Cookies For developers: They reduce the load on the server by keeping the data in the user’s local storage. You know the preferences of the user, such as the language, UI theme, or currency. Since the data is stored in the user’s hard drive, the data loss due to server failure is minimal. For the user: The ‘related searches’ area, which shows you the topics related to what you’ve searched previously, takes the help of cookies. The items added to the cart are remembered with the help of cookies. You don’t have to log in to the same website again and again. During submitting forms, the cookies remember the data entered previously, such as the name, contact number, e-mail, etc. Which seriously saves a lot of time. There is a wide usage of cookies for making one’s experience better. The Downside Of Cookies For developers: The size of a cookie cannot exceed more than 4096 bytes(4KBs). So only a fixed amount of data can be stored there. Users can delete the cookies at any time. The developers have to bother about such cases. Only data with plain text is allowed in the cookies. So complex fields cannot be merged. For a single website, the maximum amount of cookies that can be deployed is 20 (for most browsers). Not more than that. For the user: The cookie takes the local storage of the desktop. So, if you surf a lot on the internet without removing the past cookies, the cookies can take up some space. Resulting in slowing down the desktop. Since the transfer of cookies takes place a lot of time between the hard drive and the website’s server. The chances of your internet activities and history becoming available to the public increases. Most websites collect information with cookies in a lawful manner. But some of them take without any valid reasons. Which further sometimes used to sell the information to some third-party organizations, who may misuse the information provided. How To View or Delete Cookies To view the saved cookies in your browser: First, go to the Settings of your browser. You’ll get the section for Privacy and Security. Under that section, go to Cookies and other site data. After that, for viewing the cookies and the data, just click the All cookies and site data button. On that page, you’ll see all the cookies stored on your hard drive. To delete the saved cookies in your browser: On the same page, under "All cookies and site data" you’ll have a button that says remove all at the top. Just tap that for deleting all the cookies. The second method is that while deleting the browsing data, just check the box saying cookies and other site data and then clear it. Just in case you don’t have much time to delete the cookies, at least just look at the third-party cookies and alter them. Also, keep your cache clear and be careful while visiting websites that are not secure. Only assume the worst-case scenario every time. If you were starving and clicked this for your craving, a big sorry from my side. This was not that cookie :)

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Time Blocking, Color-Coding, Batching, and Calendar Audits Calendars had been there with us for thousands of years now. The first recorded calendar being the Babylonian calendar consisting of 12 Lunar Months starting when a crescent moon was sighted on the western horizon at sunset. With the advent of computers, calendaring software came into usage that enabled users to view their schedules and book meetings with other people. The term itself is taken from the , the term for the first day of the month in the Roman calendar, related to the verb “to call out”, referring to the calling or the announcement that the new moon was just seen. — calendar calends calare Wikipedia In the 1960s, a typical executive spent around 10 hours doing meetings. Since then, as the complexity of organizations and the nature of work we do has increased, we now spend about 23 hours a week doing meetings.¹ Post COVID, this has grown further and research states that people now attend 13% more meetings.² More than ever, we are now living in times where our days are governed by what is there on our calendar. And at times, this can be overwhelming. However, there are four techniques that can help your reclaim your control over your time. Time Blocking A lot of us maintain a to-do list, be it on an offline notebook or an online tool such as Asana, Google Keep, or Todoist. Time Blocking takes this a step further and you actually block time on your calendar to do specific tasks. Benjamin Franklin is one of the early practitioners of Time Blocking. Time Blocking helps and you’re not spending all your time reacting to inbound requests. It also helps you prioritize as you get a realistic view of how much you can get done in a day. A secondary benefit is that it of figuring out what you should be working on next as you have a plan in place. ensure you have time left to go through your planned to-do items reduces the cognitive load The way I go about time blocking is every Monday, start of the day, I list down my top three priorities and then block time for the tasks against them in the week. I do consciously leave out open time slots for flexibility and serendipity. Color-coding Color coding involves assigning colors to your calendar events based on priority, projects, or the kind of activities they are. A color-coded calendar . A regular calendar treats all events as the same. Whereas in the real world, a time block for an interview might require a completely different energy level and mindset as opposed to a time block for an executive review. helps you understand how your week looks like Batching Batching is a productivity technique in which you club together similar activities to reduce the context switching overhead. You can bucket your tasks as per projects you are working on, people you will be spending time with, or the nature of the activities such as is it a a time to write do code reviews or write product specs. You can extend the system to batch similar meetings too, wherever possible. Review session, a 1–on-1 with a report, or A variation of batching is having themes for your days and focus your tasks and meetings around the designated theme. Twitter and Square’s CEO Jack Dorsey³ is one of the well-known practitioners of theming Calendar Audits Calendar Audits between how you perceive you spend your time viz-a-viz how you actually spent your time. uncover the gap You can run audits on multiple dimensions such as projects, people, and types of activities. Think of Calendar Audits as a feedback loop for your weekly planning activity. A few questions that calendar audits provide an answer to are: As a Product Manager are you spending enough time with your customers? As a People Manager are you doing enough to grow your team? Are you spending enough time on your highest priority initiatives? Are you spending your time on high-leverage activities? Is your schedule balanced and optimized for your role? Calendars help people find a common time to meet, discuss, and get work done. However, calendars have not evolved to understand the context of a person’s role and responsibilities. This means that it ends up treating every person and every open time slot as the same. With these four techniques, you can take back control of your time and design a schedule that is optimized for your goals and priorities. We're working on a side project called Mornin to simplify how people can go about applying these four techniques on Google Calendar. Do give it a spin and let us know what you think. References https://en.wikipedia.org/wiki/Babylonian_calendar https://hbswk.hbs.edu/item/you-re-right-you-are-working-longer-and-attending-more-meetings https://www.forbes.com/sites/kevinkruse/2015/10/12/jack-dorsey-productivity-secret/?sh=63e73b73136a

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Managers often have to do simple routine work or master new fields — such as analytics — on the go. This results in exhausted managers trying to find time for everything and doing a worse job than they could. But we’ve found a way to solve both problems. Skyeng co-founder Denis Smetnev tells the story. Currently, there are several internal services at Skyeng that make employees’ lives easier. This is where you go if you’re simply understaffed and need some easy tasks performed, like transcribing an audio recording or sorting data in Excel. Administrative Assistance. A team that produces designs, text, videos, and all kinds of creative projects for the whole company on demand. Content Production. If someone needs to set up and configure web analytics for a website, they can assign this work to people who specialize in it. Analysts. Developers you can involve in your project. Shared team. Every Skyeng manager can use these services in their work. The important thing is to justify their value for the business. How do these teams work? Is every project economically and procedurally successful? Why don’t we outsource? Let’s start at the beginning. How and why we came up with the internal services All the services that help us formed on their own. We didn’t sit down and think of starting a service from scratch. Still, on a certain level it was a conscious development. Our initial experience was with the administrative assistance service. I hired my first assistants when I began doing quality control. The job was to listen to operators’ conversations and fill out checklists, check off boxes. I knew I wouldn’t manage that on my own, and besides it wasn’t the kind of work to spend my time on. Any manager has a ton of diverse tasks to do. But some of those tasks are low-level. They don’t require expert knowledge, or special skills, or experience, or an MBA. They’re things like putting together a list of groups to advertise in, transcribing an interview, or transferring data into a table. A manager could do all that, but then they’d be wasting precious time on work they’re overqualified for. After all, an hour of a manager’s work is worth much more than an hour of an assistant’s work. If a manager who makes 3000₽ an hour spends two hours on filling out a table, it’ll be worth its weight in gold. Skyeng’s administrative assistance service 25 employees 3,660 work hours per month 1,600,000₽ saved per month An employee of Skyeng can assign any simple job to an assistant. Instead of a personal assistant, there is an entire service that receives assignments from all the company’s departments through a single window. Almost 50% of each month’s tasks boil down to searching for and analyzing information and processing data. The work of every expert involves many such tasks. Assistants help us do more work in less time, while we help them get started in IT. Many of the assistants end up joining the main staff. In 2020, 22 people out of 25 received such a promotion, becoming content marketers, designers, project managers, heads of teaching groups, SMM managers, and even team leaders. For example, one HR department is headed by Lyuda Hart, a former assistant. The assistance service is more than 3 years old. We have clearly worked out every process, and the economy of this project is wholly transparent. We can always see the hours spent on a task and compare the salaries of managers and assistants. In the end, everyone is happy: the managers don’t suffer from the routine and the assistants grow into experts. Recently, we began loaning our assistants out to other companies. Now their services are being utilized by Netology, IIDF, Legion Farm, MelScience. Our internal development has become a commercial product. Content Production at Skyeng 1,000 tasks per month 43 employees, not including freelancers It was in much the same way that we recently launched our internal creative agency: the Content Production department. A long time ago, we hired some terrific marketers, but the quality of our Facebook advertising remained horrendous anyway. We realized that a good internet marketer will not necessarily be a good creator, designer, or copywriter. We needed to systemize the process to help our crew and our image. To produce designs and text of equal quality, we launched Content Production: an internal service that helped marketers come up with advertising. Initially, we even called it Content Factory. Today this service generates content not just for the marketing department, but for the whole company. From small tasks like images, presentations, and text we have graduated to large-scale interteam projects like creating a brand platform and launching a show on YouTube. We produce designs, text, and videos for all kinds of purposes. We launch, test, and develop media projects. In these areas, we are the standard-bearers within Skyeng and Skysmart. Certain tasks can be outsourced. For example, you can hire a writer for a landing page. They may know their way around a landing page, but be incapable of writing a PR piece. But when you’ve got a pool of Content Production writers, you can pick a person who specializes in a particular topic. You won’t have to look for someone every single time: a manager can get a person with necessary experience — or even a team of experts — through a single window. As part of their work, every Skyeng employee can order content that will be created by professional designers, editors, copywriters, content producers, writers, cinematographers, and video editors. Managers can thus save a great deal of time on looking for a contractor or trying to do the work on their own, and receive a genuinely high-quality product. Skyeng’s analytics service 4 employees 147 tasks per month People would often come to analysts with requests like, “How do I calculate this?”, or “Help me configure landing page analytics.” This was a distraction for the main analytics team. But, since the inquiries were simple, the team allotted them to a go-to person who would address them quickly. Later this became a service, one the analysts are prepared to share with clients today. The opposite happened with the Market and User Research department. At one point it, too, functioned as a service: anyone could come there and order a study of the market or of customers’ behavior. Initially we had two subdivisions: Market Research, which functioned as a single structural unit, was not tied to any team and performed tasks on demand, and User Research, in which all the researchers were attached to, and only took assignments from, their respective product teams. Last year, Market Research got more or less disbanded. The simple reason was that the assignments dried out: where at one point everything that happened at Skyeng used to be a mystery for the company, over the years we’ve made everything transparent, analyzed the markets, worked out a development strategy and figured out what to launch. At this stage we don’t need strategic research — only assistance in launching new divisions. We decided that this would be best accomplished from within those projects. Ideally, every structure would have its own Market Research departments, which is how it’s done with User Research. But the general Market Research department is no longer functioning, and its employees are now in other positions within the company. Why sometimes you can’t avoid outsourcing. Shared Team: 11 developers 302 tasks so far this year For the entirety of 2020, we had another service: Shared Team. This is a standby team of developers who can become involved with a project at any stage. The team initially had two types of clients: product teams that needed to go over and above the plan, and non-product teams that didn’t have developers of their own but needed to automate something, build a bot, etc. As time passed, the team’s resources stopped being enough to cover every demand, the developers’ workload grew exponentially, and it became unclear which tasks to prioritize. By the year’s end we finally decided to turn to external resources; in this case it was justified. We made our deals not with standalone freelancers but with companies that have some of their developers standing idle, so we’re just buying out their time. But for subcontracting to work, it’s important to organize technical supervision of the outside employees. They’re not alone with the work; Skyeng’s team leaders fully supervise the tasks and onboard the developers. In other words, the workforce is external while the management is ours. As of early 2021, that’s the plan. But none of it is set in stone. We’ll see if this approach works and, perhaps, we’ll make other changes. No need to fear compromise and new ideas; you have to look for the optimal solution. Internal services as a superpower One of the most stressful things for a manager is to put a team together. To figure out who you need, whether the people you’ve got are competent or not. It’s challenging, and it requires a lot of resources. And when you always have established teams at the ready, that really pumps you up. You’ve noticed by now that there are two types of services at Skyeng. The assistants are there to take the weight off highly skilled employees’ shoulders, enabling them to not do work any junior employee can handle. Their value is in saving skilled employees’ time and energy for us. Meanwhile, Сontent Production and developers are an extra power to be engaged. They are people with a great deal of expertise. They don’t just mechanically perform their tasks; they get deeply involved in them and influence business processes. They are capable of saying, “No, your idea isn’t gonna work. It won’t solve the problem. You have to approach it from a different angle,” and then coming up with an alternative. So our skilled employees are rid of the routine and have at their disposal a team of professionals they could never hire on their own. Who, in turn, do quality work on a turn-key basis. Why, in the end, do we develop our services internally? It sounds paradoxical, but it’s easier that way. In order to do quality work, people need to be immersed into our process. Skyeng employees know all about it, whereas we’d have to explain it to outsourcers. Speedy onboarding. We would need to grant outsourcers access to every system, make sure the data is secure, and remember to revoke access once the job is done. Granting access to data always means the risk of a leak. The only way to avoid that is to not entrust outsiders with something that may leak. Especially if it’s something that can impact the brand and its reputation. Data security. Internal services, unlike freelancers, can always be relied upon. A freelancer could disappear or turn down the job at any moment. When we assign the work to our services, we always know it’ll be done on time. Workload management. You could hire an assistant or a designer, but if they had only one client within the company, they’d be underutilized. It’s expensive and disadvantageous to keep a motion designer employed if they’re not 100% occupied. Financial gain. Managers don’t have to waste time communicating. Our services mean a single entry point and a black box. Once a manager has brought in the assignment, they know it’ll be done, and they don’t have to care about how. Work on a turn-key basis. . We set our own rules. We have a single standard that’s applied to the work of our analysts, designers, assistants and content producers. This way, we can guarantee everyone who comes to us the same level of service. Quality standardization Right now, we can definitely state that our internal services are beneficial for the company. But a service’s effectiveness grows in parallel with the number of its clients, when it’s utilized by your colleagues from other departments and not just you. As a service gains scale, the cost of creating a unit of content becomes lower. If all these workers were in different teams, we would need more of them, and they would cost the company more while working less efficiently. We often go to analysts, developers, and the Content Production crew when we ourselves lack the necessary expertise. A manager can’t know and be able to do everything; that’s okay. But together we are a force to be reckoned with.

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E-commerce is capturing an ever-increasing market share of shoppers. In addition to the requirements of managing a physical store (like tracking inventory), e-commerce stores have additional challenges, which include getting the product to the customer, using a payment processor, and building relationships with customers. All of these tasks require specialized infrastructure, which in turn interact with your database. A lot of your store’s efficiency and effectiveness rests on the decisions you make about structuring and storing data. In this article, we’ll explore the pros and cons of a NoSQL database for your e-commerce application and use the most popular document store option, MongoDB, in our examples. Note: This data modeling exercise is a response to the Hacker News comments about a previous post we published about building a scalable e-commerce data model. NoSQL Databases and MongoDB MongoDB supports (atomicity, consistency, isolation, and durability) transactions, and its cloud offering is (Payment Card Industry Data Security Standard) compliant. It's one of the best NoSQL options for e-commerce. ACID PCI DSS MongoDB also saves documents in a JSON-like format, which means it's very simple to convert queries and results into a format your frontend code understands. This removes the need to write object-relation mappers (ORMs). Further, MongoDB scales extremely well; it's to be distributed across multiple machines. NoSQL databases don't come with enforced schemas. Introducing new fields is fast because the database doesn't need to be told you're going to change the format or even the existence of a field. It simply saves what you tell it, no fuss. designed While this is great for growing businesses where products and checkout workflows evolve rapidly, it does require lots of care to ensure you don't create data that will confuse future developers and application versions. Before starting to model your system, be aware that MongoDB doesn't start with access control. Don't let this default catch you by surprise. before you write real data! PCI compliance requires that some cardholder information is encrypted at rest and in motion. You can enable Transport Layer Security/Secure Sockets Layer (TLS/SSL) to secure network traffic. Enable access control encryption We'll cover at-rest encryption later in the article, but before going live with any site using MongoDB, go over the to make sure you're up to date on best practices. security checklist Data Modeling a Digital Storefront with NoSQL There’s an almost endless array of features you can build out for an online store, but for the purposes of this article, I’ll focus on modeling just a few: your product catalog, user information, payments, and orders. Product Catalog In order to sell things, you need to record what you have so clients can browse before committing to a purchase. The bare essentials for a product document are the and a unique identifier like a . It's also common to include a description, the quantity you have available, and an image file. price sku All examples are run from in the and should be adopted to a driver for your application. Mongo shell ( { : , : , : , : { : , : , : }, : , : [ , ], : } ) db .inventory .insertOne item "journal" price 9.99 qty 25 size h 14 l 21 w 1 features "Beautiful, handmade journal." categories "writing" "bestseller" image "items/journal.jpg" This will return a verification message like this: { : , : ObjectId( )
} "acknowledged" true "insertedId" "600e814359ba901629a14e13" If you don't supply MongoDB with an field, it creates one using an . The field is a unique, immutable, indexed identifier. To make your example more lifelike and show the flexibility of MongoDB, use the command and the returned to accommodate two related products with slightly different features, and throw in a promotional offer. _id ObjectId _id updateOne _id ( 
    { : ObjectId( ) }, 
    {
        $ : { : , : , : , : },
        $ : { : , : [ , ], : [ { : , : { : NumberDecimal( ), : }, : , : { : { : , : , : }, : [ ], : [ , ], : , : }
            }, { : , : { : NumberDecimal( ), : , : NumberDecimal( )
                }, : , : { : { : , : , : }, : [ ], : [ ], : , : }
            } ]
        }
    }
) db .inventory .updateOne _id "600e814359ba901629a14e13" unset image 1 size 1 qty 1 price 1 set item "journal" features "Inner pocket" "Durable cover" skus sku "154A" price base 9.99 currency "USD" quantity 20 options size h 14 l 21 w 1 features "72 sheets of premium lined paper" colors "brown" "red" ruling "wide" image "images/journal1.jpg" sku "154B" price base 14.99 currency "USD" discount 4.00 quantity 15 options size h 18 l 22 w 2 features "140 sheets of premium paper" colors "brown" ruling "unlined" image "images/journals.jpg" Notice that we changed the structure of the field from a string to an array. This highlights the powerful (and dangerous) flexibility of NoSQL databases—you can radically change how data is formatted without a peep from the database. In that regard, command-line SQL is scary, but command-line MongoDB is terrifying. features We also settled on a format for . Choose one and stick to it throughout your application. monetary data You can get a head start on product modeling by scouting the data required by major providers like and . You can also check out Fabric's to learn how an e-commerce platform like Fabric handles product modeling. Google Marketplace Amazon Marketplace product information management (PIM) system Query Design Practices The goal with MongoDB is to structure your schema so your application returns all the data it needs in a single read query. Adding complexity in MongoDB often involves adding to a record. is important for efficiently scanning for information. Without an index, MongoDB must perform a collection scan, examining every document in a collection before returning the result. Index the fields you'll use to regularly search for products. embeddable documents Indexing Users Once you have an idea of what products you want to offer, think about how to model your users. You want to store information that will allow you to build an ongoing relationship with a customer, such as being able to display items relevant to them. If you’re selling physical products, every customer must have contact information. Here's a simple user profile for a store that needs to ship a physical product. Because you want to enforce unique email addresses for users and use that field to look them up, you'll index that field and make it unique. You could accomplish this with a command like the following: (
  { : },
  { : true } 
) db .customers .createIndex email 1 unique But this example will use the built in field instead. Remember that the field is indexed, unique, and immutable. If a user changes their email, you’ll want to revalidate it. In this case, immutability is an asset; if a user wants to update their email address, MongoDB will demand a new collection entry, and you can be sure that your field gets reset to false. _id _id emailVerified ( { : , : , : , : , : false, : { : , : , : , : , : , : }
} ) db .customers .insertOne _id "journalfanatic@e/mail.com" fname "Journal" lname "Fanatic" hashedAndSaltedPassword "$1$O3JMY.Tw$AdLnLjQ/5jXF9.MTp3gHv/" emailVerified address country "United States" street1 "99 Main Street" street2 "Apt #3" city "Boston" state "MA" zip "74586" Customer profiles are a tricky part of e-commerce because they represent people. Unlike products, people are out of your control and constantly changing. They change addresses, want packages delivered to work, and forget their passwords. This is when you have to start thinking about protecting personally identifiable information (PII) and start working toward . Becoming PCI compliant is a big undertaking and often one of the compelling cases for using a third-party provider that is already compliant. Payment Card Industry (PCI) compliance Let's update our simple example to start handling these issues. First, you'll update the zip code, then add a new delivery address and a date modified field. ( 
    { : },
    { $ : { : , : { : , : , : , : , : } },
     $ : { : new Date() }
    }
) db .customers .updateOne _id "journalfanatic@e/mail.com" set "address.zip" "60601" shippingAddress street1 "50 Work Street" street2 "Floor 16" city "Chicago" state "IL" zip "60601" setOnInsert dateModified Next, help your model accommodate a password reset request that has an expiration for thirty minutes from now (and update the field). For performance reasons, you need to be sure that embedded documents don't infinitely expand over time. dateModified If a user resets their password a hundred times, and each time it's added to the document, pulling information about that customer for a simple action (like a login) will be very resource-intensive. It's better to separate out events that can be repeated many times, like orders, site visits, and password resets into their own collection, and use to link other collections. customer document references To make a reset collection: ({ : ,
    token: ,
    status: ,
    expiration: new (ISODate(). () + ( * * )),
    requestTime: new ()
} ) db .reset .insertOne customerId "journalfanatic@e/mail.com" "493654" "requested" Date getTime 1000 60 30 Date These tables can get much more complicated very quickly, especially once you start tracking user sessions, presenting customized content, or selling products to teams of users and want to track utilization and distribution of resources. Validation Validation not be necessary for your product models, but it's absolutely a requirement for customer-related fields. Addresses, phone numbers, emails, and credit card numbers have to be validated to ensure you're not opening your site to malicious users and to prevent mistakes that stop customers from obtaining your products. might MongoDB offers tools for at the collection level. You'll also want to implement application-level validation. Validating uniqueness in MongoDB is only possible by creating an index and requiring it to be unique. A collection already exists in our example, so use to add some validation. validating schema customers runCommand ( { : ,
   validator: { $jsonSchema: {
      bsonType: ,
      required: [ , ],
      properties: {
         _id: {
            bsonType: ,
            pattern: ,
            description: }, : { : ,
            minLength: ,
            description: }, : { : ,
            required: [ , ],
            properties: {
                zip: { 
                    pattern: ,
                    description: }, : { : ,
                    description: }, : { : ,
                    description: }
            }, : " , "
         }
      }
   } },
} ) db .runCommand collMod "customers" "object" "hashedAndSaltedPassword" "address" "string" '.+\@.+\..+' "must match the email pattern" hashedAndSaltedPassword bsonType "string" 10 "must be a string ten characters long, and is required" address bsonType "object" "street1" "zip" "^[0-9]{5}(?:-[0-9]{4})?$" "must match pattern and is required" street1 bsonType "string" "must be a string and is required" street2 bsonType "string" "must be a string" description must be an object and is required As you can see, writing validation in MongoDB is cumbersome. We only validated six fields, and the code took twice as many lines as creating the record. Libraries like can make validation easier, while headless commerce APIs from third parties like Fabric] will handle data validation for you. Mongoose No matter how you decide to implement validation, it's vital for the long-term health of your application that you audit your data and create solid schema and application-level validation for any user-entered fields. Payments Modeling your payments is where the is most important. It's also the first place where you really need to reference another table. security of your application It can be tempting to include payments in the customer table by adding a nested document, but it's not wise. Payment information has specific and extremely important security concerns; it's simpler to audit your PCI compliance practices if payments are not mixed in with a lot of other data. Let's start with a naive (and dangerous!) implementation, then discuss some of the security implications that can improve the model. ( { : , : , : , : , : NumberDecimal( ), : { : , : , : , : , : }
} ) db .payments .insertOne customerId "journalfanatic@e/mail.com" status "verified" gateway "stripe" type "credit" amount 1.00 card brand "Visa" pan "4242424242424242" expirationMonth 1 expirationYear 2090 cvv 123 This is a starting point, but e-commerce experts will panic seeing this schema. All the information necessary to use this card is in your database in plaintext, which might be convenient but creates huge legal liabilities for your business. The is very clear, unless it's necessary, and like the verification code. PCI DSS don't store cardholder data never store authentication data Encryption MongoDB offers enterprise clients the ability to and perform . Any user is able to use manual to encrypt individual fields, then set to enforce the encryption. Encrypted fields are stored as binary data ( ). encrypt data files automatic client-side encryption client-side encryption schema validations subtype 6 With manual encryption, the handles applying an appropriate encryption key, as well as the encryption and decryption operations. driver for your chosen language Following the guidelines, you don’t have to encrypt your database fields if you're only storing the last four digits of the card. But be aware that any time you're bundling the Primary Account Number (PAN) with other personally identifiable information, whether at rest or in motion, all that data must be encrypted. Let's try again. PCI DSS ( { } ) ( { : , : , : , : , : NumberDecimal( ), : { : , : , : , : , : true
    }
} ) db .payments .remove db .payments .insertOne customerId "journalfanatic@e/mail.com" status "verified" gateway "stripe" type "credit" amount 1.00 card brand "Visa" panLastFour "4242" expirationMonth 1 expirationYear 2090 cvvVerified Now you've removed the authentication data and replaced it with a Boolean, truncated the card number so you're not required to encrypt other information like the expiration date. In this example, you've handled one type of payment option (credit cards), but there are many others, each with its own security requirements and data models. Research what you'll need, and the best practices for handling and storing that information. Tokenization A great way to remove some of the complexity of PCI compliance is to check if your payment processor (like ) offers a tokenization service. ) replaces all the information used in payment processing with a token string that your systems can use to track payments. Tokenization is great as it offloads PCI compliance requirements to your payment processor, reducing your liability and simplifying your code. Stripe Tokenization Here's an example of a tokenized model: ( { : ,
	status: ,
	gateway: ,
	type: ,
	token: } ) db .payments .insertOne customerId "journalfanatic@e/mail.com" "awaitingVerification" "stripe" "token" "card_1IDHBZFdjJUqVVV2gPlbz8BC" Orders Orders are where the rubber meets the road. Your customer has a profile that enables you to send them something, and you have products to send them and the ability to accept payments. The order tracks your product through the process of leaving your possession and entering the customer's hands. Orders are another data model for tracking human behavior, so they can get messy. Customers can abandon and modify orders and request refunds. This step in the example brings together all the moving parts of your model: products are purchased by customers with payments. Our model will include things that exist in other collections, like shipping addresses and discounts. In a SQL database, this information would exist as references to existing tables, but remember that in MongoDB you want all the relevant data to be returned in a single read command. It's often more efficient to make a copy of relevant information and store it in the collection. That way, when a user checks on an order, you don't have to read through multiple collections to display the information you want. orders ( { : , : , : , : , : , : NumberDecimal( ) : [ 
        { : , : , : NumberDecimal( ), : NumberDecimal( ), : NumberDecimal( ), : NumberDecimal( ), : NumberDecimal( ),
		}, { : , : , : NumberDecimal( ), : NumberDecimal( ), : NumberDecimal(. ), : NumberDecimal( )
        } 
    ], :  { :{ : , : , : , : , : , : }, : { : , : , : , : , : , : }, : , : }
} ) db .orders .insertOne customerId "journalfanatic@e/mail.com" paymentId "600e6f37aa2232f59e273082" paymentStatus "paid" status "shippedAwaitingDelivery" currency "USD" totalCost 39.85 items sku "154B" quantity "2" price 14.99 discount 1.00 preTaxTotal 27.98 tax 1.00 total 28.98 sku "154A" quantity "1" price 9.99 preTaxTotal 9.99 tax 87 total 10.86 shipping address street1 "50 Work Street" street2 "Floor 16" city "Chicago" state "IL" country "USA" zip "60601" origin street1 "1 Penn Ave" street2 "" city "New York" state "NY" country "USA" zipCode "46281" carrier "USPS" tracking "123412341234" Modeling the Whole Here are all the parts of your NoSQL e-commerce data model so far: It's an excellent start, but as I stated at the beginning of this guide, there are many facets of an e-commerce store, and we’ve barely brushed the surface. Other valid activities to the model could include adding , handling image optimization, internationalization, additional , product categorization, customer customization, subscriptions, recurring payments, taxes, and returns. product distribution channels data validation When modeling your data for e-commerce, mistakes can be costly, and customers will rarely appreciate the amount of effort that goes into creating a finely tuned database. With that in mind, you can consider of your e-commerce database to a service. You can make use of low-overhead API requests to store your data and let someone else keep up with industry best practices while you focus on improving your product. offloading the management Previously published at https://resources.fabric.inc/blog/nosql-ecommerce-data-model

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Building a MongoDB NoSQL E-Commerce Data Model

As any new technology or innovation evolves, there will always be credible companies working towards expanding the industry, and there will always be fraudulent companies looking to take advantage of new enthusiasts who do not yet know enough about the space. This is unfortunately what we've seen in the crypto industry, where scammers posing as legitimate crypto companies have defrauded investors out of more than $16 billion since 2012. Our new research project entitled " " details the impact of crypto scams over the past decade to show how massive the losses were, and how few people were brought to justice. $16 billion in lost funds has an incredibly negative impact not just on the people who were scammed, but it tarnishes the reputation of credible projects and could stagnate the industry as a whole. By closely examining these scams, however, we can find ways to recognize what scams look like and how investors and the industry can protect themselves against these threats going forward. Crypto Investor Scam Report Scams and Consequences According to the report, the first big fraud in the crypto space was the Bitcoin Savings and Trust scam. Launched in 2012, the investment scheme, run by founder Trenton Shavers, promised high returns to investors and eventually defrauded them of $97 million. More schemes and bigger losses followed, with the top five largest frauds being the following: OneCoin relied on big promises and flashy presentations to promote their token, yet no substance — not even a blockchain — existed underneath. OneCoin collected $4.4 billion of investor money, and while one founder was arrested, the other disappeared. BitConnect was an investment scheme that promised high yields — up to 1% per day — for investors who bought in at different returns levels. Legal pressure eventually led founder John Bigatton to shut BitConnect down, but not before he defrauded investors out of $2.5 billion. PlusToken was a Chinese coin that also promised high returns on investment. It gained the following of more than 2 million investors and rose to a valuation of $17 billion before the founders posted a note reading "Sorry we have run" on the ledger and disappeared. WoToken was another scam that promised high yields, a proprietary trading software that didn't exist, and rewards for member referrals. The founders, who were also associated with PlusToken, took over $1 billion from investors. Arbistar 2.0, run by Santiago Fuentes of Spain, again promised high yields generated by a proprietary arbitrage bot, but "computer errors" continued to block investors from accessing their funds. Fuentes was eventually arrested after collecting $1 billion from investors. These are just a few of the 136 crypto projects that have defrauded their investors out of $16 billion, according to the report. Have there been consequences for those scams, though? Of the 136 projects we found, criminal charges have been filed against the only 71 of the teams. Additionally, only 15 projects have had members of their team convicted and sentenced for fraud, money laundering, or other investment scheme charges. The rest of the crypto projects on our list have had no recourse taken against them. Obviously this can damage the crypto industry at large, including legitimate projects and investors who want to push the industry forward. Therefore, it's crucial that investors know how to look for red flags around new crypto projects and that the industry itself begins to build checks and balances to help purge bad actors. What Investors Can Do Investors who know what to watch for will be able to avoid any schemes that look dubious, but they need to know what to evaluate. When looking at a new crypto project, investors can do the following: Read the white paper: Any good company starts with a solid proof of concept. A well-constructed white paper that establishes the concept and how it will be executed can help show the project is credible. Avoid projects with white papers that are confusing, plagiarized, or that don't exist. Look for a working business model: Has the company tested their plan through a viable business model? An investor should check to see if the proof of concept from the white paper actually works, and a trustworthy team should be happy to show it. Find out more about the team: Having a good team behind the project will help give it credibility. First, make sure there are more than just one or two people working on the project. Look to see if they have professional bios with a portfolio of work in other areas and that they can be found elsewhere on the internet. Is the team creating value: A good start-up wants to create value for their investors and their customers, not just hype. If the team is simply promoting their project with buzzwords and fancy events, but there's nothing of substance behind it, move on. What the Industry Can Do It shouldn't just be up to the investor to do their due diligence. The industry should put safeguards in place to help investors learn more about crypto projects, and make sure scammers don't have the ability to defraud without any check to their operations. For example, have a disclosures registry where teams can provide info about their project, their history, their team members, and their business plan. Those who have nothing to hide will be willing to provide information about their business to attract new investors. And a registry could hold the industry to greater transparency that can weed out illegitimate schemes sooner, or surface scams that are trying to stay anonymous. Once the industry begins to develop and adopt better investor relationship practices — including communication, disclosures, calls, and more — it'll set a precedent for project teams around transparency. It'll also encourage investors to ask questions around the project and build a relationship with the founders. Those founders unwilling to commit send the message that they might be a scam. As we saw above, some scammers are being held accountable. But once the money's gone, it's too late. The industry needs to find ways to hold itself accountable and flag fraudulent projects early through transparency and education. Conclusion The good news is that the crypto industry has rocketed past the threshold of intolerance for these scams to put a stop to crypto’s growth. But while the report details the damage done, if improvements aren't made and checks and balances aren’t put into place, the real damage may yet come.

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Avoiding Crypto Investment Scams: The Most Definitive Guide

In the previous part, you learned what are. In this part, you will understand how Delta Transaction Log, named DeltaLog, is achieving ACID. ACID transactions Transaction Log A transaction log is a history of actions executed by a (TaDa 💡) database management system with the goal to guarantee over a crash. ACID properties DeltaLake transaction log - DetlaLog DeltaLog is a transaction log directory that holds an record of every transaction committed on a Delta Lake table since it was created. The goal of DeltaLog is to be the source of truth for readers who read from the same table at the same time. That means, parallel readers read the same data. This is achieved by tracking all the changes that users do: read, delete, update, etc. in the DeltaLog. ordered single exact DeltaLog can also contain statistics on the data; depending on the type of the data/field/column, each column can have min/max values. Having this extra metadata can help with faster querying. DeltaTable read mechanism uses a simplified . push down predict Here is a simplification of DeltaLog on the file systems from Databricks site: The DeltaLog itself is a folder that consists of multiple JSON files. When it reaches 10 files, DeltaTable does a checkpoint and compaction operations (we will dive into it in the next chapter). Here is an example of a DeltaLog JSON file from the code source test resources, each entry in the file is on JSON: { :{ : , : }}
{ :{ : , : }} "remove" "path" "part-00001-f1cb1cf9-7a73-439c-b0ea-dcba5c2280a6-c000.snappy.parquet" "dataChange" true "remove" "path" "part-00000-f4aeebd0-a689-4e1b-bc7a-bbb0ec59dce5-c000.snappy.parquet" "dataChange" true There was a total of two commits captured in this file: -it can be a delete operation on a whole column or only specific values in it. In this operation the metadata field is set to true. remove dataChange Here is a more complex JSON file example, each entry in the file is on JSON: { :{ : , :{ : , :{}}, : , :[ ], :{}}}
{ :{ : , : }}
{ :{ : , : }}
{ :{ : , :{ : }, : , : , : }}
{ :{ : , :{ : }, : , : , : }}
{ :{ : , :{ : }, : , : , : }} "metaData" "id" "2edf2c02-bb63-44e9-a84c-517fad0db296" "format" "provider" "parquet" "options" "schemaString" "{\"type\":\"struct\",\"fields\":[{\"name\":\"id\",\"type\":\"integer\",\"nullable\":true,\"metadata\":{}},{\"name\":\"value\",\"type\":\"string\",\"nullable\":true,\"metadata\":{}}]}" "partitionColumns" "id" "configuration" "remove" "path" "part-00001-6d252218-2632-416e-9e46-f32316ec314a-c000.snappy.parquet" "dataChange" true "remove" "path" "part-00000-348d7f43-38f6-4778-88c7-45f379471c49-c000.snappy.parquet" "dataChange" true "add" "path" "id=5/part-00000-f1e0b560-ca00-409e-a274-f1ab264bc412.c000.snappy.parquet" "partitionValues" "id" "5" "size" 362 "modificationTime" 1501109076000 "dataChange" true "add" "path" "id=6/part-00000-adb59f54-6b8f-4bfd-9915-ae26bd0f0e2c.c000.snappy.parquet" "partitionValues" "id" "6" "size" 362 "modificationTime" 1501109076000 "dataChange" true "add" "path" "id=4/part-00001-36c738bf-7836-479b-9cc1-7a4934207856.c000.snappy.parquet" "partitionValues" "id" "4" "size" 362 "modificationTime" 1501109076000 "dataChange" true In this example, there is the object entry - it represents a change in the table columns either an update to the table schema or that a new table was created. Later we see two operations, followed by three operations. These operation objects can have a field, which contains statistical information, such as the number of records, minValues, maxValues, and more. metadata remove add stat These JSON files might also contain operation objects with fields such as - "STREAMING UPDATE", "NOTEBOOK" if the operation took place from a notebook, isolationLevel, etc. This information is valuable for managing the table and avoiding redundant full scan on the storage. To simplify the connection between DeltaTable and DeltaLog, it's easier to think about DeltaTable as a direct result of a set of actions audited by the DeltaLog. DeltaLog and Atomicity From , you already know that atomicity means that a transaction, either happened or not. The DeltaLog itself consists of atomic operations; each line in the log (like the ones you saw above) represents an action, which is an atomic unit; These are called commits. The transactions that took place on the data can be broken into multiple components in which each one individually represents a commit in the DeltaLog. These breaking complex operations into small transactions help with ensuring atomicity. part one DeltaLog and Isolation Operations such as Update, Delete, Add can harm isolation; Hence, since we want to guarantee isolation with DeltaTable, readers only get access to the table snapshot. This guarantees all parallel readers read the exact data. For handling deletion operations, Delta postpones the actual delete operation on the files; it first tags the files as deleted and later, remove them when considered safe (similar to Cassandra, and ElasticSearch delete operations with a tombstone). In DeltaLake 0.8.1 source code, there is a comment saying that it's recommended to have the delete retention set to at least 2 weeks or longer than a duration of a job. This will impact streaming workload as well, because there will be a need to delete the actual files at some point, which might result in blocking the stream. Note: DeltaLog and Consistency Delta Lake solves the problem of consistency by solving conflicts with an optimistic concurrency algorithm. The class in charge of this algorithm is the OptimisticTransaction class. It achieves it by using that is controlled from a DeltaLog instance. Java 8 ReentrantLock Here is the code snippet: A DeltaTable instance actively uses the ReentrantLock in the OptimisticTransaction under the function. The optimistic approach was chosen here because in the big data world there is a tendency to add more data than to update existing records. It's rare to find and update a specific record, it is usually done when there was some data corruption on necessary data. doCommitRetryIteratively Here is the code snippet for the optimistic algorithm: Notice that in line 572, the program records the attempted version as the instance which is of type . in Scala represents a mutable object instance, which means we should expect its value to change. commitVersion var var In line 575, we start the algorithm: it starts the loop and maintains an counter; if it's , it will try to commit; if it fails here, that means that a file with this was already written/committed into the table and it will throw an exception. That exception is being caught in lines 592+593. while(true) attemptNumber ==0 commitVersion From there, with each failure, the algorithm is increasing the attemptNumber by 1. After the first failure, the program won't go into the first if statement on line 577; it will go straights into the on line 579. else if If the program reached the state where is bigger than the maximum allowed/configured, it will throw a exception. maxCommitRetriesExceededException exception will provide information about the commit version, the first commit version attempt, the number of attempted commits, and total time spent attempting this commit in ms. Otherwise, it will try to record this update with checkForConflict functionality in line 588. Multiple scenarios can bring us to this state. attemptNumber DeltaErrors.maxCommitRetriesExceededException High-level pseudo-code: while(tryCommit)
    if first attempt: : attempt > retries
            throw an - : retry operation
            try fixing conflicts - valid throw an retry attempt + - do commit else if number max exception exit loop else record logical return commit version or exception do commit on exceptions and version 1 if no exception end loop end To support the users, DeltaLake introduces a set of conflict exceptions that provide more information about the data and the conflicts: Let's look at some of the conflict scenarios. Two Writers: This is the case of two writers who appends data to the same table simultaneously, without reading anything. In this scenario, one writer will commit, and the second writer will read the first one's updates before adding their own updates. Suppose it was only an append operation, like a counter which both are incrementing. In that case, there is no need to redo all computations, and it will automatically commit; if that's not the case, writer number two will need to redo the computation given the new information from writer one. Delete and Read: In a more complex scenario like this one, there is no automated solution. For concurrent Delete-Read, there is a dedicated That means that if there is a request to delete a file that at the same time is being used for a read, the program throws an exception. ConcurentDeleteReadException. Delete and Delete: When two operations delete the same file, it might be due to a compaction mechanism or other operation, here too an exception will occur. DeltaLog and Durability Since all transactions made on a DeltaTable are being stored directly to the disk/file system, durability is a given. All commits are being to disk. In case of a system failure, they can be restored from the disk. (Unless there is a true disaster like fire etc and damage to the actual disks holding the information). persisted For exploring and learning about Delta, I did a deep dive into the code source itself. If you are interested in joining me, I captured it through videos, let me know if that is useful for you. What's next? Next, we will see more examples, scenarios, and use cases for DeltaLake! We will learn about the compaction mechanism, schema enforcement, and how it can enforce exactly once operation. As always, I would love to get your comments and feedback on 🐦. Adi Polak If you would like to get monthly updates, consider . subscribing Previously published at https://blog.adipolak.com/post/delta-lake-essential-fundamentals-the-deltalog/

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The DeltaLog: Fundamentals of Delta Lake [Part 2]

⚡️ The new CSS property introduce for HTML element the capability to auto-sizing. aspect-ratio all { : / ; } { : / ; } { : / ; } { : / ; } { : (width) / (height);
} .square aspect-ratio 1 1 .rectangle aspect-ratio 3 1 .video aspect-ratio 16 9 .ultrawide aspect-ratio 21 9 .intrinsicsize aspect-ratio attr attr 🗣 Without the property , only some elements have a built-in auto-sizing system. aspect-ratio 📝 For instance, the tag when has at least the width value explicitly configured will implicitly calculate the height value and vice-versa. <img /> 🤩 Now, using aspect-ratio, even a can support the auto-sizing mechanism. <div> 📣 The new CSS property is useful to create responsive interfaces. aspect-ratio 👍 Also, help the developers to apply the best practices while working with images on the web since it allows manipulates with high precision the size of a given image using its original aspect ratio, which also will, in parallel, improve the performance metrics on . aspect-ratio since will be easy to identify images with a wrong resize rule Lighthouse ⚡️ is already supported on Chrome 88. Safari is reportedly working to support it soon. Firefox and Edge are starting to consider the support. aspect-ratio Also published at https://dev.to/obetomuniz/aspect-ratio-property-on-css-7lh

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Understanding How CSS3 Aspect-Ratio Property Works

Leveling a crafter to 80 may seem straightforward to players just starting out but it can get overwhelming. While the game helpfully keeps track of where one might be in the crafting questline, it doesn’t really show all the ways one could earn the valuable XP needed. Fortunately, this FFXIV crafting guide is here to outline some of the most efficient ways to walk the road to 80. Job quests While this is a blindingly obvious suggestion, the job quests can be really helpful if you’re doing them as soon as they’re available. They will give a hefty chunk of XP for the class and even give some gear to ease the gear requirements as one increases in level. It is, however, not possible to rely on these alone. The first problem would be that they are drip-fed as the player climbs in level and don’t provide a consistent increase in XP. They even stop past level 70 which adds some challenge on the final stretch. These quests do also require the player to source their own crafting materials until level 60 which can make them expensive to keep up with. Picture Credit: FFXIV Wiki Crafting Log The FFXIV Crafting Log can be easy to overlook but can come in handy, especially at early levels. Simply put, the log will award a one-time bonus to the player for crafting each item available to their class. It’s usually not more than a convenient bonus past the early levels but can’t hurt. Collectable Turn-ins Collectable turn-ins have the player take special care in creating an item, aiming to increase its quality to the highest degree possible to gain bonuses to the rewards that they’ll get for turning the item in. While it is great for XP, it can get expensive fast, as players will need to source their own crafting materials and have the gear necessary to create the high-quality collectables FFXIV Crafting Guide: Tradecraft Leves Tradecraft Leves are repeatable content where players have to craft specific items in challenges. These reward some fairly steady XP and can be very useful in early levels. Unfortunately, these also require players to source their own crafting materials. Beast Tribes The Beast Tribes scattered around Eorzea and beyond provide XP for both combat and crafting classes. They work by finding a relevant Beast Tribe and doing the three daily quests available. While they don’t award as much XP as the Job Quests, they provide more XP than simply crafting items en masse. This FFXIV crafting guide does recommend that you do these daily to keep a steady stream of XP going. There are other benefits from doing Beast Tribes. Some of these quests, like the Namazu questline, are incredibly entertaining and it would be a shame to miss out on them. They also provide unique items for the player that range from a Palanquin carried by the Namazu and an actual tank. While they require a long questline to unlock, these are well worth pursuing for how well they grease the wheels of levelling. The Beast Tribes that level crafters are Ixali (20-50) Moogle (51-60) Namazu (61-70) Dwarf (71-80) Grand Company Supply Missions The Grand Companies can be a valuable source of equipment and XP for players to take advantage of in the early game. Unwanted items can be traded in for Grand Company Seals which can then be traded in for themed equipment. Combat classes can undertake hunts to earn themselves XP as well. For FFXIV Crafters, Grand Company Supply Missions offer Supply Missions. These award generous amounts of XP and Seals in exchange for a specific item that the player is capable of crafting. Not only does it help fill out the Crafting Log, it can be great practice for getting the crafting rotations down. Unfortunately, this source of XP can be time consuming or expensive as crafting materials aren’t provided. If one doesn’t have  Gatherer handy or the patience, they would be at the mercy of market board prices which might prove expensive. Custom Deliveries At various parts of FFXIV’s story, players will get to meet characters who need certain items crafted as part of a quest chain, similar to the Beast Tribes. Unlike Beast Tribes, however, this system resets weekly and offers up to 12 turn-ins per week and is limited to 6 per NPC. It doesn’t offer as much XP overall but it does provide Crafter’s Scrips, a currency that can be used to buy high-level crafting gear. Many of the NPCs involved in Custom Deliveries tend to have strong ties to the FFXIV’s excellent story and their quest lines often serve as an epilogue for certain plot threads which can be an added bonus. Ishgard Restoration While the Ishgard Restoration event has unfortunately concluded, it is still incredibly useful for players to level their crafters and gatherers after they’ve completed Heavensward. Operating on a separate set of items from the rest of the content, players can deliver items to NPCs in the Firmament in exchange for XP. FFXIV Crafting Guide Final Thoughts There is no limit to how much a player can turn in which allows players that enjoy long grinds to quickly level their crafters while learning the crafting rotation. Turning in items for the Ishgard Restoration also rewards Skybuilder’s Scrips, a currency useful in getting cosmetic items. Also, be sure to check out: 1. 2. 3. What are the Best Video Game Controllers of all Time? Dark Alliance to Deliver Hack & Slash Gameplay This June PS5 Controller Review: 5 Best Features That'll Blow Your Mind

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Within the Monster Hunter World (MHW) universe, there are many different items to collect that help you progress through the game, whether that be consumables perfect for avoiding death in a monster fight or crafting materials to improve and level up your armour and weapons. One of these materials is warped bone. The MHW warped bone is a rare material needed to level up your various gear and armour pieces, crucial for completing the game and fighting Monster Hunter World’s final bosses. What is the MHW Warped Bone? The warped bone is a material used to help improve various armour and weapons pieces. It is a challenging item to find with the item only located in one specific area within the game and randomly generated, meaning it is all down to luck as to whether it drops. Thus, the probability of getting a warped bone is low, meaning this item is a frustrating item to find for many players. The item is one of the rarest bone materials you can get in Monster Hunter World. Monster Hunter World Warped Bone location You can find the MHW warped bone in one specific area, . The Rotten Vale can be unlocked around midway through Monster Hunter World's main story and contains many monsters such as Odogaron. the Rotten Vale It is an area filled with monster corpses, a decomposing wasteland that is a graveyard for monsters. To access this area, you need to have completed the main story quest Radobaan Roadblock. After completing this quest, you should have full access to the Rotten Vale. You can access the Rotten Vale through either a quest mission or an expedition, with the latter being the most advised option so that you can have adequate time to find the warped Bone. The Rotten Vale is split into several smaller sections; the warped bone can be found in any one of these areas and is generated randomly. How to find the item in the Rotten Vale The item is located in bone piles throughout these areas. Bone piles are relatively common throughout the Rotten Vale. However, the chances of getting a warped bone from these bone piles are not. It is all down to luck as to whether an MHW warped bone drops. Nevertheless, when you see a bone pile, make sure to harvest its materials and hopefully, you get lucky. Although even rarer, it is possible to get a warped bone from defeating certain monsters and gathering their materials. Slaying Raphinos and Rabobann gives you the chance of acquiring the item. Defeating Raphinos grants you an 8% chance of receiving the bone, while killing a Rabobann gives you a 31% chance of the item dropping but the chances of a drop vary depending on the ranking of the quest. You can also obtain the item through several different Rotten Vale missions as base rewards. Such assignments include low-rank missions such as A Rotten Thing To Do to master rank missions like The Lord of the Underworld Beckons. The probability of the item dropping varies depending on the mission's rank, with a 12-16% chance of a Monster Hunter World warped bone dropping. You can find a list of quests that reward the item here. How can MHW Warped Bones be used? The Monster Hunter World warped bone is primarily used to upgrade your equipment and weapons. In terms of weapons, the warped bone is needed to forge most Dragon Bone weapon set's low-rank weapons. The item can also be used to upgrade several high-level armaments, such as upgrading the Pulsa Shotel 11 into the Pulsa Shotel 111 long sword. Likewise, the Warped bone can make high-level armour, such as the Odogaron Alpha set and the bone alpha set. Finally, the warped bone can create a range of charms needed to give your character a buff during intense boss battles. Such charms include the master's charm and the blaze charm. A complete list of charms, armour pieces and weapons that require the MHW warped bone can be found here. Final Thoughts Conclusively, this is one of the rarest items in the game. If you are lucky enough to get your hands on some, they can be invaluable in constructing the best charms, weapons and armour in MHW. Also, check out: What are the Best Video Game Controllers of all Time? Fallout 4 Halo Armor Mods: From the ODSTs to NOBLE Team 6 Games That Everyone Should Play at Least Onc

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How to Find the Monster Hunter World (MHW) Warped Bone and How to Use It

Whenever people review the role of business analysts, one thing they do consider is the tools and techniques they employ for performing their data analytics. The key performance indicator for the success of a business is measured by its approach to data. If the business is using data driven approach, then it means that they are utilizing their business data efficiently by performing some data analytics and predictive analytic softwares and deriving meaningful information in the forms of charts and reports. These reports and insights help them identify key areas in operations to improve and increase their worth in the market. Almost all available business intelligence and reporting tools have features to aggregate, organize and assemble data from different data sources across the organization and make it accessible for the data analysts to delve in and generate reports that would highlight the aspects of business that was left unnoticed before. They try to answer important questions about the business performance following their data trail from the previous years. They identify the common mistakes that might be affecting the business performance and what steps can the management take to maneuver the business in the right direction. All this become one notch easier when the data reporting and analytic software is embedded in the existing business workflow environment. The popularity of embedded data analytic software emerges from a great number of benefits over the traditional software some of which are familiarity and ease of use not to mention added security. These features are making business analysts move towards embedded solutions whenever possible to tap the best analytic experience and increase work productivity of their business. “Analytics software is uniquely leveraged. Most software can optimize existing processes, but analytics (done right) should generate insights that bring to life whole new initiatives. It should change you do, not just how you do it.” - what Matin Movassate, Founder and CEO at Heap Analytics What is embedded data analytics? Embedded data analytics moves away from traditional data analytics and allows user to create and run reports and perform data analytics from within the existing business software. The data analysis and reporting features are directly embedded into the software and works within the umbrella of the existing business work environment. This give added flexibility and familiarity to the users to work from their familiar environment and they can start working with minimal training and support. When working in a business scenario, data and reports are part of their daily work schedule. It makes sense to add these functionalities into the already running business software instead of using stand alone or plug in softwares that might have a completely different look and feel and the user is not familiar with the interface. In this scenario, an embedded data analytic and reporting solution is most suited as it can get the data reporting and analysis features integrated directly into the running system. Features of embedded analytic tools Embedded analytic software solutions usually have all features as that of traditional softwares but some common features that stand out and attract data analysts to make it their choice are listed here. Going through this list would give data analysts an idea of what features to look for when they go software hunting for their business needs. Compelling data visualizations At the base of all data analysis and reporting softwares is the feature to present data in the form of meaningful visuals and infographics that can help data analysts track the record of the business in different areas and identify areas of focus that need attention of the management, which in turn can use these data figures to make decisions about the business products and other entities. “Visualization gives you answers to questions you didn’t know you had.” – Ben Schneiderman Creative data dashboards One important feature that is very useful when data analysts want to monitor and compare multiple reports at the same time is the ability to create customized dashboards. These dashboards are very helpful in monitoring time critical data that may be changing rapidly and needs constant attention.  Data dashboards lets users add and remove reports as required and manipulate the reports layout and positioning according to their own personalized choice. This gives added comfort to the data analysts for performing the data analytics. Varied data report layouts Most embedded data analytic and reporting software offer a variety or report layouts for data analysts to choose the most appropriate report format to present the report. Sometimes the report format would change based on the type and format of data its presenting so the data report formats are flexible and have variety to accommodate different types of data requirements. Multiple deployment options Embedded data reporting solution may have options for cloud based deployment in which case your data will be hosted remotely and report running and other overheads are handled on a remote site. This takes the burden off the shoulder of businesses to give them a chance to expand their business without increasing their budget to upgrade their hosting platform or hardware servers. Minimal staff training The cost and time for staff training after making an addition to business software can be reduced to a minimal by using an embedded data analytic and reporting software. The users are already familiar with the existing business software and do not feel the pressure of yet another software training in this case. Minimum training can get end users started on the reporting tool and they can learn as they explore. Data modelling and insights Embedded reporting and data analytic tools now come with the feature to create and maintain different data models and experiment with available data modelling techniques to research and fine the best data model for their needs for getting data reports and insights faster. Data querying Data querying is another feature that can help business analysts with predictive analysis and what if analysis to the business data. Certain questions are identified that are critical to business operations and better performance. Data analysis is performed to answer these questions and identify trends and patterns in the previous years. This helps the management to take long term and short term decisions and modify their business strategies to find out what is working best and help increase their business growth. What do business analysts need? Business analysts need to be able to perform data analysis and reports in a way that increases work productivity within the organization and utilize their capitals and assets to improve business sales and increase their product worth in the market. To achieve this end, business analysts prefer embedded data analytic and reporting solution because it will give them the following advantage over the traditional standalone softwares: Increased productivity due to informed decisions taken on the base of data insights embedded into core application and business processes. Improved user experience as they work in a familiar business environment. Maintenance and upgrade options are also easier to implement and adopt by users. Embedded data analytic software offers increased data security as the software works within the umbrella of existing software and same security protocols are adopted. Reduced cost of implementation is there because the software is directly embedded into the business software and backend is usually managed through cloud server. Examples of best embedded data analytics and reporting tool Finally, here is a list of example softwares that provide best features of embedded data analytics and reporting tools. Dotnet report builder With customization and convenience at the top of their agenda, dotnet report builder lets end user design and generate completely customized and powerful analytics and reports. This .net reporting tool is full of power packed features that help data analysts perform their task with efficiency and convenience. The solution is embedded directly into business application and runs from within their framework. Izenda Izenda offers an embedded business intelligence software solution for its customers. It embeds natively into the business software and offers the business analysts powerful features to analyze data through meaningful insights and reports. The reports are customizable and can be created using the drag and drop interface. SAP crystal reports SAP Crystal report is an embedded data reporting software that can be integrated in any business application to run reports and provide data analytic features. It monetizes data and generates useful insights to help business analysts make decisions that impact business growth. Zoho analytic Zoho analytics offers a range of data reporting and analytic capabilities. The users can work with data by generating customized reports and meaningful insights that can help data analysts with data driven business analysis. The embedded analytic features of charts, widgets and other report layouts make it an attractive tool in the market for embedded data analytics and reports.

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