Abhishek Kumar, CSPO®

The Data Analyst's Guide to Reproducibility (Part 1): https://wix.to/3cWX9tq #newblogpost #dataanalysis #reproducibility #newdataanalysts #careergrowth #datadocumentation #dataanalysistips

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🆃🅷🅴2️⃣🅰🅼🆃🅰🅻🅺🆂 "Welcome to The2AMTalks, where late-night concepts meet early-morning work!" 𝐓𝐨𝐩𝐢𝐜: Cumulative Percentage in SQL 𝐂𝐨𝐧𝐜𝐞𝐩𝐭 𝐞𝐱𝐩𝐥𝐚𝐧𝐚𝐭𝐢𝐨𝐧: Cumulative Percentage in SQL tracks the running percentage of a value over ordered rows, offering insights into its contribution to the total as rows are processed sequentially. 𝐐𝐮𝐞𝐫𝐲 𝐞𝐱𝐩𝐥𝐚𝐧𝐚𝐭𝐢𝐨𝐧: The 𝗥𝗼𝘂𝗻𝗱((𝘀𝘂𝗺(𝗿𝗲𝘃𝗲𝗻𝘂𝗲) 𝗼𝘃𝗲𝗿 (𝗼𝗿𝗱𝗲𝗿 𝗯𝘆 𝗱𝗮𝘁𝗲) / 𝘀𝘂𝗺(𝗿𝗲𝘃𝗲𝗻𝘂𝗲) 𝗼𝘃𝗲𝗿 ()) * 𝟭𝟬𝟬, 𝟮) formula calculates the percentage contribution of the cumulative revenue for each row relative to the total revenue, rounded to two decimal places. • 𝗦𝘂𝗺(𝗿𝗲𝘃𝗲𝗻𝘂𝗲) 𝗼𝘃𝗲𝗿 (𝗼𝗿𝗱𝗲𝗿 𝗯𝘆 𝗱𝗮𝘁𝗲): Calculates the cumulative sum of revenue up to the current row, ordered by the date. • 𝐒𝐮𝐦(𝐫𝐞𝐯𝐞𝐧𝐮𝐞) 𝐨𝐯𝐞𝐫 (): Computes the total sum of revenue across all rows, without any specific order. • (𝘀𝘂𝗺(𝗿𝗲𝘃𝗲𝗻𝘂𝗲) 𝗼𝘃𝗲𝗿 (𝗼𝗿𝗱𝗲𝗿 𝗯𝘆 𝗱𝗮𝘁𝗲) / 𝘀𝘂𝗺(𝗿𝗲𝘃𝗲𝗻𝘂𝗲) 𝗼𝘃𝗲𝗿 ()) * 𝟭𝟬𝟬: Divides the cumulative revenue up to the current row by the total revenue. Multiplies the result by 100 to convert it into a percentage. • 𝐑𝐨𝐮𝐧𝐝(..., 𝟐): Rounds the calculated percentage to two decimal places for readability. 𝐄𝐱𝐚𝐦𝐩𝐥𝐞 𝐟𝐫𝐨𝐦 𝐨𝐮𝐭𝐩𝐮𝐭: The 𝗰𝘂𝗺𝘂𝗹𝗮𝘁𝗶𝘃𝗲_𝗽𝗲𝗿𝗰𝗲𝗻𝘁𝗮𝗴𝗲 for '𝟮𝟬𝟮𝟰-𝟬𝟰-𝟬𝟯' is (4500 / 7000) * 100 = 64.29%. Follow my intuitive way of doing analysis in 𝗦𝗘𝗣 𝗦𝗲𝗿𝗶𝗲𝘀 [https://lnkd.in/gKGxRuSH] Let me know your commonly used formula(s). #dataanalyst #businessanalyst #datamodelling #dataengineer #analytics #dashboard #etldeveloper #powerbi #tableau #aws #logicbuilding #analysis #sql #python #dataenginner #learning #businessintelligence #opentowork

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𝐆𝐨𝐨𝐠𝐥𝐞 𝐅𝐨𝐫𝐦: https://lnkd.in/gfjzXpSi Want to enhance your Data Insights game? Our upcoming 𝐃𝐚𝐭𝐚 𝐈𝐧𝐬𝐢𝐠𝐡𝐭 𝐂𝐨𝐮𝐫𝐬𝐞, taught by GMAT expert Manan Kumar, 𝐛𝐞𝐠𝐢𝐧𝐧𝐢𝐧𝐠 𝐨𝐧 𝐀𝐩𝐫𝐢𝐥 𝟐𝟎. 𝐂𝐨𝐦𝐦𝐞𝐧𝐜𝐞𝐦𝐞𝐧𝐭 𝐃𝐚𝐭𝐞: 𝟐𝟎 𝐀𝐩𝐫𝐢𝐥, 2024 🔍 Features of the Course: - 𝐌𝐞𝐭𝐡𝐨𝐝𝐢𝐜𝐚𝐥 𝐭𝐞𝐜𝐡𝐧𝐢𝐪𝐮𝐞𝐬 to succeed in Data Insight tasks - ⁠𝐓𝐞𝐬𝐭-𝐭𝐚𝐤𝐢𝐧𝐠 𝐭𝐞𝐜𝐡𝐧𝐢𝐪𝐮𝐞𝐬 specific to the Data Insight domain - ⁠C𝐨𝐦𝐩𝐢𝐥𝐞𝐝 𝐥𝐢𝐬𝐭 𝐨𝐟 𝐃𝐚𝐭𝐚 𝐈𝐧𝐬𝐢𝐠𝐡𝐭 questions to increase expertise emphasis on understanding 2-part analytic puzzles and MSR in particular - 𝐄𝐱𝐚𝐦𝐢𝐧𝐞 𝐭𝐡𝐞 𝐩𝐢𝐭𝐟𝐚𝐥𝐥𝐬 𝐨𝐟 𝐝𝐚𝐭𝐚 𝐢𝐧𝐬𝐢𝐠𝐡𝐭𝐬 and learn how to avoid them. Take advantage of this chance to improve your data insights skills! 𝐓𝐡𝐞𝐫𝐞 𝐚𝐫𝐞 𝐨𝐧𝐥𝐲 𝐚 𝐟𝐞𝐰 𝐬𝐥𝐨𝐭𝐬 𝐚𝐯𝐚𝐢𝐥𝐚𝐛𝐥𝐞. For inquiry 𝐩𝐥𝐞𝐚𝐬𝐞 𝐫𝐞𝐚𝐜𝐡 𝐨𝐮𝐭 𝐭𝐨 MAHI . 𝟗𝟔𝟓𝟎𝟏𝟑𝟐𝟐𝟔𝟎. #ProfessionalDevelopment #DataInsight #gmat #bschool

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Switch between days, weeks, and months in reports⭐💡 You can now view your line chart data by day, week, or month, depending on the level of detail you need. More on : https://lnkd.in/ggDbQiPT #analytics #dataAnalysis #GA4 #whatsnew #googleanalytics

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Begin an immersive journey of exploration with us as we delve into the nuances of crafting drill-down bar charts in Tableau. In this blog, consultant Calvin Gao guides us through the process, unraveling the details behind this powerful visualization tool. ➡️Read here to enhance your Tableau skills and take your data analysis to the next level: https://ow.ly/JAJB50RT0mX

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Data science is as common as numbers. Wherever there is data, analysis, and interpolation, there is a scope for data science. The insights from these analyses can reveal untouched areas for improvement. This is especially true in sports management. Data science in sports is becoming a billion-dollar industry. Read more about how data science, AI, and ML are redefining our understanding of sports in our most recent blog. Read it here: https://lnkd.in/d58AFvVn #ai #ml #sports #aiinsports #blog #airtics

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Google Analytics vs Mixpanel: A Comprehensive Guide In the digital age, the importance of data analytics for businesses cannot be overstated. Google Analytics and Mixpanel stand out as two of the leading platforms in this realm, each offering unique insights and functionalities. This guide aims to provide a detailed comparison between Google Analytics and Mixpanel, tailored for business users seeking to leverage these tools for enhanced data-driven decision-making. Read more

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Topic - From Data to Decisions: Exploring Predictive Analytics at Walmart Date & TimeMay 9, 2024 07:00 PM Speaker- Jayantilal Bhanushali Lead Data Scientist at Blenheim Chalcot India Registration- https://lnkd.in/dGDH6pXE What You'll Learn: 1. Understand the basics of predictive analytics and its significance in the retail industry. 2. Discover how Walmart collects and analyzes data from various sources to predict trends, demand, and customer behavior. 3. Learn about the technologies and tools Walmart uses to process and analyze data, including AI and machine learning platforms. 4. Explore real-life examples of how predictive analytics has transformed various aspects of Walmart's operations, from inventory management to personalized marketing. #setupskills

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Keeping your analytics game strong means never resting on your laurels! 🚀 Embrace new techniques, tools, and insights to stay ahead. And hey, if you're feeling stuck, we're here to help you innovate and improve. 📊💡 Got thoughts on analytics trends? Share 'em below or hit us up @DakeSolutions! 🤝 #AnalyticsEvolution #DataDriven #InnovateWithDake #dakesolutions

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Introducing Three Key Terms in Tableau Are you ready to dive into the exciting world of data visualization? Understanding the essential terms in Tableau is the first step towards unleashing the power of your data and creating impactful visuals that address real-world problems. In this post, we'll explore three key terms that will elevate your Tableau game and make your analysis more insightful than ever before. So, let's embark on this journey together as we unravel the significance of these terms and uncover how they lay the foundation for exceptional data storytelling. Buckle up, and let's dive in! 1.Data connection: The left pane of the data source page displays details about the data that Tableau Desktop connects to. Under the connection tab is the related details of the source file. E.g File name, sheet names etc. 2.Data Source: A Tableau Data Source is the link between the source data and Tableau. It may contain multiple Data connections to different databases or files. The data source comprises the actual data: live or extracted data, connection string to the underlying database, description of fields, and metadata changes such as calculations, renamed fields, hierarchies etc. 3.Data Models: the data model is a diagram that tells Tableau how it should query data in the connected database tables. Data Models consist of connection information, queries that are to be executed to retrieve the data and any Metadata. The data model is used as the foundation for creating further analysis in Tableau Tableau can have a complex learning curve but well designed curricula like the Resa Data Bootcamp help you to learn these concepts more interactively. With mentors and Tableau ambassadors as your guide, you can master Tableau like a pro. Learn more at resagratia.com/bootcamp #ResaDatabootcamp #DataVisualization #Tableau #DataStorytelling #DataAnalysis

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Ever wondered what the blue and green pills in Tableau actually mean? Let’s get into it. In our latest blog post, we’ll simplify and explain: - The core difference between discrete and continuous data - Why Tableau uses blue for discrete and green for continuous - How these data types impact your visualizations - Common misconceptions about dimensions and measures Whether you're a beginner or a seasoned Tableau user, this article will help you solidify your understanding of these essential concepts. Read the full article here: https://bit.ly/3VPa6pi

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Interested to know the best 10 platforms to study Data Analytics in Agra? check out the detailed course overview https://buff.ly/3XwM2dt 👍 #dataanalytics #courses #iimskills

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Thinking to go Bayesian for MMM, Experimentation or Causal Inference ? You may want to read this article before doing so. https://lnkd.in/gXC8wYtr #marketingmixmodeling #experimentation #causalinference #martech

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If you are asked to find top 5 top selling product and you have used Limit 5 Well this seems technically right! But if you think from business perspective, there are two major issues - 1. There can more than 5 products which can be in the top 5 list. But putting a limit, you restrict to only 5. So, that’s an incomplete solution. 2. ⁠this code is not optimised for production because it will take more time to execute in a large dataset resulting in inefficient implementation. Better to use window functions like dense_rank to solve this problem. These are small but very crucial nuances that proves to be make or break in the interview. SQL as a language is simple but without right business understanding, you might not solve the right problem. I am conducting the a business analysis with SQL bootcamp to help you incorporate business fundamentals to your sql knowledge. Start learning at just 999/-. Register here - https://lnkd.in/grZemXDd Atul Anand

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DID YOU KNOW???... Tableau is a powerful tool that can significantly benefit businesses in various ways. Here's how: 1.Data Visualization: Tableau excels at turning raw data into visually appealing and easy-to-understand charts, graphs, and dashboards. This capability allows businesses to gain insights from their data quickly and make informed decisions. 2.Real-Time Analytics: With Tableau, businesses can analyze data in real-time, enabling them to respond promptly to changing market conditions, customer preferences, and business trends. This agility is crucial for staying competitive in today's fast-paced business environment. 3.Interactive Dashboards: Tableau's interactive dashboards empower users to explore data dynamically, drill down into specific metrics, and uncover hidden patterns or correlations. This interactivity fosters deeper insights and better understanding of business performance. 4.Data Integration: Tableau seamlessly integrates with a wide range of data sources, including databases, spreadsheets, cloud services, and big data platforms. This flexibility allows businesses to consolidate data from multiple sources and gain a comprehensive view of their operations. 5.Predictive Analytics: Tableau supports advanced analytics capabilities, such as trend analysis, forecasting, and predictive modeling. By leveraging these features, businesses can anticipate future trends, identify potential opportunities or risks, and make proactive decisions to drive growth. 6.Empowering Decision-Makers: Tableau empowers decision-makers at all levels of the organization by providing them with access to timely, relevant, and actionable insights. Whether it's executives, managers, or frontline employees, Tableau ensures that everyone has the information they need to make informed decisions. 7.Enhanced Customer Insights: By analyzing customer data with Tableau, businesses can gain a deeper understanding of their customers' behavior, preferences, and needs. This insight enables businesses to personalize marketing efforts, improve customer service, and drive customer loyalty and retention.

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