If you feel that your digital transformation initiatives are stuck in the planning phases, you are not alone. Digital transformation is not a one-off project on an executive?s roadmap but is a constantly evolving culture. So let?s make digital transformation possible in your organization.Cultivating an agile mindsetCulture is the game and it is the most difficult thing to change. Culture maintenance is as strenuous as culture change. For an executive who is leading a digital transformation in the organization, culture change, should become an agenda item forever and maintain it forever. An executive needs to monitor culture like any other metrics 24 x 7 x ?Every Minute?. Companies often fall into the trap on not investing time effort and money on changing the culture and this happens when the leadership is focused on quantifiable ROI based metrics. This happens because ROI based metrics are easy to quantify. CEO?S, CMO?S, COO?S, CFO?S all should believe and invest time and money in changing the culture and make the organization ready for an agile mindset and when they all stop speaking the language of finance is when the digital transformation actually starts happening. Finance metrics are equally important but they have to be measured separately. Management commitment to drive digital transformation with a secured investment will kickstart innovation at a much faster rate than waiting for your employees to build a business case around digital economy adaption. Paying emphasis to build people talent and digital competencies should be a focus area for a digital transformation leader.Communicate, Communicate &amp; Communicate and then launchCommunication to the employees why digital transformation is required in an organization and how will it be done is also important. Putting big posters and innovative messages of digital revolution across an organization are proven to be effective for many companies. Creating a digital transformation playbook and making it available openly in the organization can help as well. The ideal place for it is the internal employee portal or the global communications platform for the organization. Setup a launch date and encourage all employees to be a part of it.Launch digital transformation as a lighthouse project. The term lighthouse project refers to a model project that aims, besides its original purpose, to have a signal effect for numerous follow-up projects as they look towards it for inspiration and guidance. In companies, this term is used for projects intending to change direction or restructure. This project has to be always on and the road map of this project should influence the rest of the projects in the organization. Build a cross-function team across the organization to deliver this project. Make the employees with the longest duration in the organization as change agents and advocates.Adapt Open Source TechnologiesThe new breed of innovative startups uses new agile business models and modern technologies like cloud computing, Blockchain, Real-time analytics, Deep Machine Learning. Most of these technologies are based on open source and that is the way the organization should start the digital transformation. These solutions are Free, don?t cost anything rather than to prove a business case. Some organization will need enterprise support but leading open source technologies to provide support element and is cheaper than monolithic software licensing agreements. I do agree that maintaining the status quo for business operation and keeping the lights on should be the top priority for executives but to balance out the budget between operations and innovation will drive transformation.Data-Driven Culture to build personalized customer experienceKeeping Customer at the center of every decision you make in the organization and using data as a vehicle quadruples digital transformation in an organization. Amazon, Google, Airbnb and Netflix and many startups that grow exponentially are pioneers in transforming insights into data-driven action. Airbnb leverages data to improve their search and services but also to improve their hiring processes. Airbnb characterized data by giving it a human touch: Voice of customers. They translated data coming out of customer interactions as the voice of customers and made this as part of their culture. They invented a term ? Datum. A datum is a record of an action or event, which in most cases reflects a decision made by a person. They build customer journey?s leading to a decision to say ?make a booking? and then learn from. It is a metric that actually tells you what your customer like and don?t like. This is a perfect example of how you can make a direct connection of your customer with the data you generate in your organization. The organizations that connect their data with customers and then make the voice of the customers as the key metric, as well as a culture, wins Just wins. Another example, Amazon uses data to automatically personalize user experience by leveraging customers past purchases. This will lead to a definite outcome for Amazon, that is increased sales. Netflix leverages customer interaction data from their app to present them with movies and show that they like and this will again lead to a definite business outcome that is increased user engagement. In recent years Netflix has become a giant in the creation of original content and data is a key ingredient in deciding what type of content they generate based on user engagement metrics. Leveraging the organization data to make a business decision is easier said than done. 1?2?3 of data to achieve maximum value is : Make an inventory of your organization?s data. It is a difficult task but has to be done once only. Doing it correctly with all stakeholders involved is critical ( again a culture thing to achieve ) Leverage on ?low hanging fruits? first. Take the datasets which are most easy to get hold of and can create the most impact. The example is clickstream data. This data can be acquired easily but can make the most value to a business, as described earlier. Make data transparent in your organization. This is the most difficult thing to achieve especially if you are in a regulated industry like healthcare, finance etc. But if you have your employee?s sign all proper agreements that most of the organizations do, there is not too much to worry about. If these steps are done correctly, make your employee?s responsibility to move the needle. Gain insights and leverage data to make business decisions.Kickstart your digital transformation journey today.

Vin Patel

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Digital Transformation

Building a digital transformation culture in your organization leveraging data.

Multi-channel and multi-screen browsing is the nature of the current digital economy. Consumers are likely to have engaged with your marketing initiatives on several channels and devices before they commit to a purchase.Attribution models that contribute towards the dynamics between channels and devices allow analyzing the full journey to purchase or a call to action and attribute the right credit to each event, making marketing spend decisions for digital leaders, far more accurate and financially viable. Digital attribution is one of the core fundamentals for a successful digital marketing transformation Digital attribution is the set of events based on user actions. These events or set of actions contribute in some manner to the desired digital marketing results. Each of these events is assigned values according to its importance in marketing and its impact on consumers. Digital attribution specifies what combination of events involves users in the desired behavior, mostly referred to as conversions. Leveraging Digital Attribution and make data-driven decisions is foundational to digital transformation.This article covers the basics of digital attribution from a marketing angle as a quick read for executives and digital transformation leaders.The current application of attribution marketing has emerged from the transition of marketing from traditional to digital ways. The field is highly affected by large data collected through digital channels such as online surveys, social media data, conversion, emails etc.Its main purpose is to quantify and study the effects each advertising impression leaves on the purchase decision of the user. Subsequent to analyzing and studying what influences customers more, marketers optimize media for conversions and compare the importance of different media channels for marketing, such as E-mail, affiliate marketing, social media networks, display ads, and others.Analyzing the whole conversion path across the whole marketing mix eliminates the accuracy challenges of analyzing data from isolated marketing means. Usually, attribution statistics is utilized by marketers to map future ad promotions and campaigns by evaluating which media assignments (ads) were the most cost-efficient as shown by metrics like CPA (effective cost per action).<h1 id="models-of-attribution">Models of attribution</h1>Rapid growth and popularity of digital advertisement and online marketing have concluded in a large amount of user data for tracking, ROI and effectiveness of conversions. These new tendencies have affected the way marketers measure the effectiveness of marketing and advertising. The trends have also opened a new door to development of new marketing metrics that are CPI (cost per impression), CPC (Cost per click), CPA (cost per acquisition/action), and click-through conversion. For this reason, a number of attribution models have emerged with time since the explosion of data and devices have boosted up the creation of attribution technology. Digital attribution is very important because it assists advertisers in analyzing behaviors and responses of customers.The types of attributions are:Single source attribution Also known as single touch attribution, allocates all credit to the single event or action, for instance, the last channel used to show the ad, last click or initial click. Single attribution model does not justify and contribute to all elements involved in creating results. This is the reason model isn?t considered verified and accurate especially by Google. Fractional attribution This attribution model comprises of consumer credit, U-curve models, and equal weights. Here equal weight based models assign the same amount of credit to all media channels and media mix, consumer credit involves studying guesswork or past experiences of customers to assign credits, and whole credit is allocated to first and final click in U-curve where idle actions are ignored across conversion path. Algorithmic attribution This model of attribution utilizes proprietary algorithms to allocate conversion among all touch points before conversions with the help of auto scripts to locate where credit is unpaid. Model is started from very first event level and assesses converting and non-converting paths crosswise all media channels. After that weights are combined to figure out hidden associations and correlations inside marketing.These are the high-level attribution models that can make your marketing data more meaningful and useful in your digital transformation journey.Our last article covers on <a href="https://medium.com/digital-transformation-now/how-to-build-a-digital-transformation-culture-in-your-organization-498397801b59" rel="noopener">How to build a digital transformation culture in your organization leveraging data</a>. It articulates the need to make customer-centric journey?s the center of your digital transformation.

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Digital Marketing

What does Attribution mean in Digital Marketing Transformation?

In the United States alone, adults spent an average of 3 hours, 35 minutes per day on mobile devices in 2018. By 2019, mobile surpassed TV as the medium attracting the most consumed minutes. Teenage and Millennials internet users spent an average of 4 Hours daily on their mobile devices.Overall Effects on Health :Smartphones are a source to emit electromagnetic waves. The WHO/International Agency for Research on Cancer (<a href="https://www.iarc.fr/" rel="noopener nofollow">IARC</a>) has deemed radio-frequency electromagnetic waves as ?possibly carcinogenic to humans? and associates it with cellphone use.Majority cellphone users complain of discomfort at least in one area of upper extremities, back or neck.Headaches, fatigue, distraction, inattention are the most common symptoms of overtime on digital devices. Eye tension or insomnia after using a smartphone for more than 2 hours is also the most common symptom. The day you use smartphone 1 hour before going to bed, it will take you more time than average to go to sleep.Chances of accidents become higher when you are distracted by a smartphone while driving. That?s the reason why there are heavy fines on distracted driving.Children have the potential to be at greater risk than adults for developing brain cancer from cell phones. Their nervous systems are still developing and therefore more vulnerable to factors that may cause cancer.Prolonged use of the smartphone can damage our hearing abilities in the long runThe smartphone makes our brains lazy. Nowadays people rely more on the smartphone search a.k.a Google than their own brain powerYou will be surprised, but your cell phone can carry more germs than the toilet seatSome tips that you can follow on the daily basis<ul><li>Socialize more with friends without cell phones.</li><li>Practice ?Devise time-out? every day ( Start with 2 hours). Encourage your family to put the phones in the middle of the table during a meal. Make a habit to eat without cellphones.</li><li>Once you get used to the devise timeout strategy, try to utilize that time on personal skill development ( learn something new). This will make you more motivated to reduce devise time, eventually.</li><li>Alternate direct cellphone use by wearing earbuds.</li><li>Replace looking at your smartphone before going to bed with a reading habit.</li><li>Eat food rich in omega-3 fatty acids ? Examples are Salmon, Walnuts, and Kiwis</li><li>Ask your self, do you know the directions, phone numbers before you reach out for your phone. Try to use your brain, not the device</li></ul>From the celebrities side, I am a huge fan of <a href="https://en.wikipedia.org/wiki/Arianna_Huffington" rel="noopener nofollow">Arianna Huffington</a> and her advocation on devise detox. Her books <a href="http://a.co/d/2LQctfW" rel="noopener nofollow">Thrive</a> and <a href="http://a.co/d/aIpLGO7" rel="noopener nofollow">The Sleep Revolution</a> are worth reading. A huge initiative was taken by her in partnering with Samsung to release the thrive app. The app actually disconnects you from your phone and reconnects you to yourself. Worth checking. Note: I am no way affiliated with ThriveSources:www.emarketer.com

Digital Detox Is As Important As Exercise

<h2 id="write-and-showcase-your-technical-skills">Write And Showcase Your Technical Skills</h2><h3 id="why-should-i-write"> Why Should I write? </h3>Showcase your skills You have the expertise, but so does millions of others on sites like LinkedIn. How can you stand out? Writing for us will allow you to promote your content on your social media profiles, build your own audience, take them to any other platform if you would want to leverage them for an online course, ebook, in person event etc. Any readers that choose to ?follow? you will be a jointly owned audience between yourself and Techfastly. You will be able to message them for content on Techfastly or any other platform that you wish to migrate them to. In return we ask for that your articles be:<ol><li>Original (We will use a variety of tools for this purpose)</li><li>Be rich, actionable and insightful </li></ol>If you share your expertise with us by filling in the form below (you can upload or resume or link your LinkedIn Profile), we can provide you specific topics that we are looking to get content on. In terms of quality, here is a link to some articles that we deem as high quality: 1) <a href="https://techfastly.com/how-to-build-a-digital-transformation-culture-in-your-organization-leveraging-data/">https://techfastly.com/how-to-build-a-digital-transformation-culture-in-your-organization-leveraging-data/</a>2) <a href="https://techfastly.com/what-does-attribution-mean-in-digital-marketing-transformation/">https://<span style="border-color: rgb(229 231 235/var(--tw-border-opacity)); --tw-translate-x:0; --tw-translate-y:0; --tw-rotate:0; --tw-skew-x:0; --tw-skew-y:0; --tw-scale-x:1; --tw-scale-y:1; --tw-transform:translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-border-opacity:1; --tw-ring-inset:var(--tw-empty, ); --tw-ring-offset-width:0px; --tw-ring-offset-color:#fff; --tw-ring-color:rgb(59 130 246/0.5); --tw-ring-offset-shadow:0 0 #0000; --tw-ring-shadow:0 0 #0000; --tw-shadow:0 0 #0000; --tw-shadow-colored:0 0 #0000; --tw-blur:var(--tw-empty, ); --tw-brightness:var(--tw-empty, ); --tw-contrast:var(--tw-empty, ); --tw-grayscale:var(--tw-empty, ); --tw-hue-rotate:var(--tw-empty, ); --tw-invert:var(--tw-empty, ); --tw-saturate:var(--tw-empty, ); --tw-sepia:var(--tw-empty, ); --tw-drop-shadow:var(--tw-empty, ); --tw-filter:var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow);">techfastly.com/what-does-attribution-mean-in-digital-marketing-transformation/</a>3) <a href="https://techfastly.com/digital-detox-is-as-important-as-exercise/">https://<span style="border-color: rgb(229 231 235/var(--tw-border-opacity)); --tw-translate-x:0; --tw-translate-y:0; --tw-rotate:0; --tw-skew-x:0; --tw-skew-y:0; --tw-scale-x:1; --tw-scale-y:1; --tw-transform:translateX(var(--tw-translate-x)) translateY(var(--tw-translate-y)) rotate(var(--tw-rotate)) skewX(var(--tw-skew-x)) skewY(var(--tw-skew-y)) scaleX(var(--tw-scale-x)) scaleY(var(--tw-scale-y)); --tw-border-opacity:1; --tw-ring-inset:var(--tw-empty, ); --tw-ring-offset-width:0px; --tw-ring-offset-color:#fff; --tw-ring-color:rgb(59 130 246/0.5); --tw-ring-offset-shadow:0 0 #0000; --tw-ring-shadow:0 0 #0000; --tw-shadow:0 0 #0000; --tw-shadow-colored:0 0 #0000; --tw-blur:var(--tw-empty, ); --tw-brightness:var(--tw-empty, ); --tw-contrast:var(--tw-empty, ); --tw-grayscale:var(--tw-empty, ); --tw-hue-rotate:var(--tw-empty, ); --tw-invert:var(--tw-empty, ); --tw-saturate:var(--tw-empty, ); --tw-sepia:var(--tw-empty, ); --tw-drop-shadow:var(--tw-empty, ); --tw-filter:var(--tw-blur) var(--tw-brightness) var(--tw-contrast) var(--tw-grayscale) var(--tw-hue-rotate) var(--tw-invert) var(--tw-saturate) var(--tw-sepia) var(--tw-drop-shadow);">techfastly.com/digital-detox-is-as-important-as-exercise/</a> If your content is only theoretical and a collection of what exists already on the web, it will not be accepted. <hr> Definitions:Minimum Length - The article should be min 1000 words.Minimum Reads - Each visit to your article page where a visitor has spent at least 3/4th of the recommended reading time and scrolled to the bottom of the page per Google Analytics (75% depth - <a href="https://support.google.com/tagmanager/answer/7679218?hl=en">https://support.google.com/tagmanager/answer/7679218?hl=en</a>) Minimum Comments - The only ?Comments? that will count as valid comments will be comments on the Techfastly platform. Each comment would have to be valid, value add ?comment?. Comments along the lines of ?Great Post? etc. will not count and an author's own comments will not count either. These thresholds have to be reached within 30 days of publishing an article. Once an article is published, it will become the exclusive property of Techfastly. <hr><h3 id="get-visibility-for-your-next-consulting-assignment-or-job">Get visibility for your next Consulting Assignment or Job</h3>In the near future we do intend to start a Consulting gig/Job board. Your writer profiles will be a key component of how potential employers or clients will find you. Unlike traditional sites, we will have options for Remote roles, Part time roles, Time zones you would be open to working in. By having robust, in depth content and your own following, you will be able to stand out from the crowd and future proof yourself for this impending launch.<h3 id="get-in-touch-with-us">Get in touch with us</h3>Publisher : Mindtrades Consulting 9513 Oswald Ln, Charlotte , 28277 North Carolina USA

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Web Monetization

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Web 3.0, also known as the "Semantic Web," is a vision of a decentralized, machine-readable web that allows for greater interoperability between different systems, devices, and websites. This vision involves the use of common data formats and protocols that allow different systems to easily share and understand data, as well as the use of artificial intelligence and machine learning to improve the ability of computers to understand and process web content.One of the key features of Web 3.0 is the use of structured data, which allows for greater precision and accuracy in the representation of information on the web. This structured data can be used by computers to more easily understand and process the meaning of web content, enabling a wide range of new applications and services.Web 3.0 also involves the use of decentralized technologies, such as blockchain, to enable the creation of decentralized applications (DApps) and decentralized autonomous organizations (DAOs). These technologies allow for the creation of distributed networks that are not controlled by a single entity, enabling a wide range of new possibilities for collaboration and innovation.Currently, Web 3.0 is still in the early stages of development, and there are not many statistics available on its usage. However, it is expected to have a significant impact on the way we use the internet in the future, with the potential to revolutionize industries such as finance, supply chain management, and more.There are also potential drawbacks to Web 3.0, such as the possibility of increased complexity and the need for specialized knowledge and skills to build and use decentralized applications. Additionally, there are concerns about the security and reliability of decentralized systems, as well as the potential for them to be used for nefarious purposes.Overall, Web 3.0 represents a significant evolution in the way we use the internet, with the potential to enable a wide range of new applications and services that are not possible with current technologies. While it is still in the early stages of development, it has the potential to revolutionize the way we interact with the web and with each other online.Here is a comparison table between Web 3.0, Web 2.0, and Web 1.0:<figure class="table"><table><thead><tr><th>Feature</th><th>Web 1.0</th><th>Web 2.0</th><th>Web 3.0</th></tr></thead><tbody><tr><td>Purpose</td><td>Information access</td><td>Information sharing and collaboration</td><td>Machine-readable data and AI-powered understanding</td></tr><tr><td>Examples</td><td>Static websites</td><td>Social media, wikis, blogs</td><td>Decentralized applications, semantic search engines</td></tr><tr><td>Key technologies</td><td>HTML, HTTP</td><td>AJAX, APIs, RSS</td><td>Structured data, blockchain, artificial intelligence</td></tr><tr><td>User experience</td><td>Passive consumption</td><td>Active participation and collaboration</td><td>Personalized and intelligent experiences</td></tr><tr><td>Interactivity</td><td>Limited</td><td>Increased</td><td>Further increased</td></tr></tbody></table></figure>Web 1.0, also known as the "Static Web," was the first iteration of the World Wide Web and was focused on providing access to information. Websites were primarily static, with little interaction or collaboration between users.Web 2.0, also known as the "Dynamic Web," introduced a range of new technologies that enabled increased interactivity and collaboration between users. This included the use of technologies such as AJAX, APIs, and RSS, which enabled the creation of interactive and dynamic web applications such as social media, wikis, and blogs.Web 3.0, also known as the "Semantic Web," represents the next evolution of the web, with a focus on machine-readable data and artificial intelligence-powered understanding. This includes the use of structured data and decentralized technologies such as blockchain, which enable the creation of decentralized applications and organizations. It also involves the use of artificial intelligence and machine learning to improve the ability of computers to understand and process web content, enabling the creation of personalized and intelligent user experiences.Use Cases of Web 3.0One example of a real-world use case for Web 3.0 is the use of decentralized applications (DApps) built on blockchain technology. These DApps can be used to create decentralized marketplaces, supply chain management systems, and more. For example, OpenBazzar is a decentralized marketplace built on the Ethereum blockchain that allows users to buy and sell goods and services without the need for a central authority.Another example of a real-world use case for Web 3.0 is the use of artificial intelligence and machine learning to improve the accuracy and effectiveness of web search engines. For example, the search engine Hakia uses natural language processing and machine learning to understand the meaning and context of search queries, providing more relevant and accurate search results.Web 3.0 technologies have the potential to significantly change the creator economy by enabling new ways for creators to monetize their content and for consumers to discover and support creative work.How Web 3.0 is changing creator's economyOne way in which Web 3.0 could change the creator economy is through the use of decentralized applications (DApps) and decentralized autonomous organizations (DAOs). These technologies enable the creation of decentralized networks that are not controlled by a single entity, which could allow creators to directly monetize their content without the need for intermediaries such as record labels, publishers, or streaming platforms. For example, the decentralized platform Steemit allows creators to earn cryptocurrency for their content, and the DAO Gitcoin allows creators to receive funding for their work through crowdfunding campaigns.Another way in which Web 3.0 could change the creator economy is through the use of artificial intelligence and machine learning to improve the discovery and promotion of creative work. For example, the use of AI-powered recommendation algorithms could help to surface more relevant and diverse content for consumers, while the use of machine learning to analyze user data could help creators to better understand and target their audience.Overall, Web 3.0 has the potential to significantly change the creator economy by enabling new ways for creators to monetize their content and for consumers to discover and support creative work. However, it is still in the early stages of development and it is not yet clear exactly how these technologies will be adopted and used in practice.

Web 3.0

Web 3.0 - A Primer

Data Discovery Algorithm Techniques that you can coach your data teams on.

Data being the new oil in 2020, many enterprises around the world are now mature in big data practices and a data-first approach. The organizations have now been able to store massive data generated by there organization in some kind of data lakes, hubs or on-premise / public cloud. With big data comes the big responsibility to manage, organize, secure the data.Over the years, big enterprises gather hundreds of data hubs and the data becomes disparate to a level that you cannot use it. This means the organization has data, in fact, lots of data ? say big data. This data being big is still of no value as it is incapable of driving business results. According to Forrester, 74% of firms say they want to be ?data-driven,? but only 29% are successful at connecting data to business value. In 2020 Industry maturity is at a stage where storing the data has been accomplished for many organizations but drawing meaningful insights into that data in a timely fashion(real-time) is still a challenge.In big organizations, the data is collected by multiple channels and the same data can have different fields and different definitions based on the source of origin.To date, there is no defined way to automate the meaning of data in real-time. Many big companies have tried to solve this approach. The most innovative solution today in the market are podium data, waterline data.IBM is also a key player. The approach these companies use is to detect the headers of the data and capture the data type of the data. Sometimes it would even use a bit of NLP to come to a potential accurate meaning of data. But, most of the time, the business meaning of the data has to be manually mapped. Data discovery platforms would detect the headers to a certain level and then will provide a semi-automated way to define the data. Manual intervention to define the business definitions of each field is still a common practice in today?s world of artificial intelligence and machine learning.The most innovative technology companies like Apple, Google, Amazon, and Microsoft ( recently ) growth is dependent on their ability to utilize the data of their customers in almost near real-time and also to handle the data securely is a critical part. As this is the secret sauce to their individual success story, the methodology is different for different companies. Tools might be available as open-source but it is difficult to understand ? How they do it end to end?Being an open-source technologist and an innovator, I try to solve these kinds of problems for the industry and share.Like the famous Eureka, one day I thought why not create open-source algorithm ideation for data discovery that can be utilized by data teams around the globe.<h2 id="outline-of-the-data-discovery-algorithm-">Outline of the Data Discovery Algorithm :</h2>So consider the piece of code sitting between the source of the data and the destination of the data. Call it a data discovery filter. This filter fundamentally eliminates the need for costly ETL/ELT &amp; Metadata management Tools and the implementation nightmare that a CEO or CTO goes through when doing digital transformation or legacy modernization in a complex organization.The data is filtered in 2 stages or states: First Stage ( Data Discovery and Standardization ) and Second stage ( Change Data Discovery &amp; Distribution standards )<figure class="kg-card kg-image-card kg-width-wide kg-card-hascaption"><img src="https://iaxds62ruoojbg1k4180.cleaver.rocks/images/posts/f6c51ea56a6134255966a232c6cbd9a2.png" class="kg-image" alt loading="lazy"><figcaption>Data Discovery Algorithms Stages or States</figcaption></figure><h3 id="first-stage-methodology-">First Stage Methodology :</h3>The first stage is when the data discovery filter detects the data. The Algorithm first detects the type of the file Is the data coming from a database( tabular) or is an image, audio, video, document. It can even be a script, geospatial data or an API. After the data file and type are detected the data is scanned to just capture the header and first 5 data elements. The Algorithm then maps each data element with 5 standard datatypes - Integer, Float, Character, String or Boolean. A further classification can happen by leveraging modern machine learning methodologies to find the data if it is a Name, Telephone Number, Social Security Number. The data can be then classified as a PII ( Personal Identifiable Information) or a Non-PII. PII information can be tokenized or scrubbed based on the need. Finally, a clean metadata file is generated with information on the data. If you are wondering that can this be done in real-time and on the fly, the answer is yes, it can be done. Yes, a data engineering culture is needed in your organization to do it. This is better than spending millions of dollars on expensive vendors.<h3 id="second-stage-methodology-">Second Stage Methodology:</h3>The second pass is the clean version of the data and it tracks the data for changes and creates a standardized format of any data so that the data becomes meaningful and distributable to numerous channels in the organization. This will be a true data democratizationFor example, if a data is coming to the filter, unchanged, the second pass will ignore it, if a data distribution format is created. If the same data enters the second stage changed it goes back to the first pass to refresh the metadata with changed data attributed.The second pass is the final form of data and it has the 2020 standard data distribution format: JSON destination mappers like: send it to an API, or send it to a BI dashboard and so on. XML is created so that legacy data sources can be feedback back with clean data if needed.The Data is a unique and most valuable asset to an Organization and the algorithm mentioned above has to be made relevant to each organization. If this approach is implemented correctly, the time to market and utilize the organizational data improves drastically.The organization that can comprehend its data and the signals/insights that it generates is the organization that leaps ahead of its competition. Every unicorn startup that would have challenged your industry would have somehow solved this challenge inhouse.<h3></h3>

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