Yashica Sharma

On real note, Power BI has in one way been limited has a business tool, where business analyst makes use of this tool to express their way out in their business. Beyond this as a sustainability data analyst, this can be use to get different information at different level. as I will be giving different insight to which this can be used and how the dashboard can reveal fantastic information about the nature of the work done. below is dashboard that represent a community, total number of infected cocoa trees per hectare, total number of hectare and type of disease infestation.

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In your Analytics career you can choose between 1. working within a single industry or domain, or 2. jumping around between different industries There are advantages to both! Sticking to one industry: - You probably get more replies when applying - You hit the ground running faster in a new job - Your domain knowledge compounds over time Jumping around: - Wider pool of job openings available to you - Get exposed to a wider variety of tools & methods - On average, it helps you grow more as a generalist Based on your experience, what else would you add? And what do you prefer? #data #analytics #career

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🤔 Have you ever wondered "What the heck is ATTR()?!" in Tableau?   It basically works like this:   IF ISNULL([field]) THEN   NULL ELSEIF MIN([field]) = MAX([field]) THEN   [field] ELSE   "*" END.   In other words, within all the variables defining a Mark within the Rows, Columns and Marks shelf (in other words, your SQL "GROUP BY"), this function tells you whether the Dimension in question is a unique ATTRibute of that Dimension grouping.   Get it?   If it has 1 value, you get that distinct value. It is an *attribute* of your Mark.   If it has multiple values, you get a *.   If all are null, you get null.   I created an example to clarify (link in comment).   An NBA team can have more than 1 All Star.   Example Viz: ✔First tab shows the number of teams (30) and players per team in 2019. ✔The second tab shows teams that have 1, 2, or 3 All Stars (not all teams). ✔The third tab (the post image) shows for which teams Player Name is, and is not, an ATTRibute. In other words, is a team had a single All Star, that name is listed. Teams with multiple All Stars have a * listed. The table also shows the MIN and MAX to show the names of available All Stars for comparison to the IF/THEN above in this post. The combination of these two fields lists all All Star players except for The Golden State Warriors, who have 3. Since there is no such thing as a "MID" text function, you lose sight of Klay Thompson unless you create some sort of crazy LOD calc like I did for "Remaining Player" ✔The last tab shows how you can use ATTR as a meaningful filter - in this case, for teams with >1 All Star.   HTH   🏗→🧠 Build to Learn!   💭🚶‍♀️🚶‍♂️ Follow for more.   #tableau #data #analytics #VizoftheRay

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NEW Button Slicers in Power BI | 3 Examples You Don’t Want to Miss! Thanks, Bas Dohmen for making a great video

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🌟 Enhancing Data Security with Power BI: Row Level Security (RLS) 🌟 In today's data-driven world, ensuring that sensitive information is only accessible to authorized users is crucial. That's where Power BI's Row Level Security (RLS) comes into play. 🔐 What is RLS? Row Level Security (RLS) allows you to control access to data at the row level in Power BI. By implementing RLS, you can ensure that users only see the data that is relevant to them, based on their roles and permissions. 🚀 Why Use RLS? ✅️Data Confidentiality: Protect sensitive information by restricting access to specific rows of data. ✅️Improved Performance: By filtering data at the source, you can enhance report performance. ✅️User-Specific Insights: Deliver personalized reports and dashboards tailored to individual users or groups. 🔍 Example Use Case: Imagine a sales dashboard where you want regional managers to see only their respective region's data. By setting up RLS, you can restrict each manager’s access to only their region's sales data, ensuring confidentiality and relevance. 💬 Have you implemented RLS in your Power BI reports? Share your experiences and tips in the comments! #powerbi #DataSecurity #BusinessIntelligence #RowLevelSecurity #DataAnalytics

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A data analyst and a social media nut case both tell stories, but what’s the difference? Data analyst digs up the data and tells a story based on relevant and concrete facts. A social media nut case tells a story first and then tries to find edge cases data points to support it. Don’t you agree ? #data #analysis #friday #thoughts

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Have you heard of the Back 2 Viz Basics challenge? These tips on colour courtesy of Shreya Arya gives great insight into how to use colour in data viz! How do you use colour in your projects? #datadna #data #powerbi #tableau

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Analytics is simple in theory. Analytics in practice is another matter 🙃 Why is it simple? It's only 3 steps: 1. Understand business problems 2. Select the right technical solutions 3. Analyze, build and influence to drive outcomes What makes it so hard in practice? - Data itself is messy and something is always breaking - Implementing solutions is never straightforward - Some people are data-driven, others are not - Different people have different incentives - Stakeholders don't understand our work The list goes on...what else would you add? #data #analytics

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Possibly One of the Most Underrated Features of Tableau Cloud: ↳Tableau Pulse It won't: - Provide the full interactive experience of dashboards - Replace custom reporting for complex analysis - Offer in-depth visual exploration for every dataset But it does: - Speed insights with rapid access to critical metrics - Empower users by focusing on key, actionable information - Boost decision-making with easily consumable data at a glance Tableau Pulse is perfect for those moments when fast, impactful insights are the priority.

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True! I will never understand the battle between tools. A personal preference should never be enforced as a standard, especially when there is a steep learning curve. 'How steep a learning curve' is different for each person. At the end of the day, as a data professional, the job doesn't end with data management; it extends to effectively communicating that data. Sure, new tools like Tableau or Power BI represent advancements, but if they are not efficient at the moment, then they are not. Do you unlearn it? No. But you must be flexible enough to understand what works and what doesn't at any given time. 'But what about advancement?' This happens in segments, and eventually, everyone gets there. But not at your pace.

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👋 Hey Data Nerds! 🤓 Almost every day I see a new 'Data Analyst' proudly sharing their work, only to find that their entire 'analysis' is just basic aggregations, followed by showcasing the top 5 from each category as if it’s groundbreaking insight. 👎 Let’s be honest: That’s not analysis. That’s just a report. 📊 (And don’t get me started on the analysts who skip data cleaning altogether. Why should I be excited about your 'top 5 sales by year' that is full of incorrect data?? But that’s a topic for another day... 😉) ➡ If you really want to dive into analysis, think beyond the surface. Explore the 𝐇𝐎𝐖 and 𝐖𝐇𝐘 behind the numbers. ❓ Ask yourself: • How can we fix this? • How can we achieve similar goals for different categories? 🧠 To all aspiring Analysts: Embrace the challenge of true analysis. Don’t just calculate averages and print reports – dig deeper, ask questions, and tell compelling stories with your data. 📚✨ ---- Hey, I’ve been there too. Early in my journey, I made similar mistakes and thought my reports were incredible insights that nobody had ever seen. That’s why I’m sharing this now. 🎯Focus on the data that really tells a story and skip the metrics without meaning. (unless those metrics were specifically requested) --- Keep pushing boundaries and 💪📈 𝐍𝐞𝐯𝐞𝐫. 𝐒𝐭𝐨𝐩. 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠. #DataAnalysis #DataScience #ContinuousLearning #DataStorytelling #Analytics #Analysis

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“Hey, #GenAI, can you get me instant insights from my #UnstructuredData?” Join the Qlik Insider webinar on 9/17 to see #QlikAnswers in action. With Qlik’s new plug-and-play GenAI-powered knowledge assistant, ask questions and get personalized, contextually relevant, and reliable answers from your own unstructured #data. https://bit.ly/3XorX7x

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This morning, I came across a post by Martyn Booth about the new INFO.VIEW DAX function in Power BI, introduced in the October release. I just implemented it in one of my reports, and it’s super cool! No more boring manual documentation—this function fully automates the process. Very useful function Check out his blog here: https://lnkd.in/dxJMjXQn #PowerBI #DAX

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Exciting news! Visual calculations are now available in Power BI, making it easier than ever to perform complex calculations directly on your visuals. With visual calculations, you can write DAX that feels like writing English, using functions like RUNNINGSUM and MOVINGAVERAGE to perform calculations that were previously difficult or impossible. But what really sets visual calculations apart is their flexibility. Did you know that these functions are actually shortcuts to more powerful window functions like OFFSET, INDEX, and WINDOW? This means you can tweak the behavior of your visual calculations to get exactly the results you need. #powerbi #dax #datavisualization #analytics #dataanalyst #datascience #reporting #interviewquestions #sql #dataanalysis

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🤔 Did you know there are 5 custom formats for Months in Tableau?   Here they are:   M - month number without leading 0 MM - month number WITH leading 0 MMM - month 3 character abbreviation MMMM - full month name MMMMM - single letter abbreviation   That last one can help when you are really tight on space.   🏗→🧠 Build to Learn!   💭🚶‍♀️🚶‍♂️ Follow for more.   #tableau #data #analytics #VizoftheRay

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How to create Table, Listing, and Figure (TLF) Shells: The Statistical Analysis Plan (SAP) and associated TLF shells are 1A and 1B when it comes to the deliverables the biostatistician produces during the study. The SAP is the written language version of the statistician telling any reviewers of the clinical trial how the data was analyzed (what populations were used, what statistical techniques were implemented, how missing data was handled, etc.). The Shells then, are the physical representation of what the written language says. The Shells give the programming team something to program towards AND give the CSR development team (Sponsor, Medical Writer, Medical, etc.) an idea of what the final outputs will look like. Here is how to ensure you create shells that are clear and meaningful to everyone: 1️⃣ Start with the SAP - as you write the SAP and any time you specify a table, figure, or listing will be generated, make a mark in the SAP for yourself. That mark is to tell you that you are calling for an output to be created. You can then create a table of contents for all the outputs the SAP is calling for. Remember, the SAP and Shells should be a 1:1 mapping exercise - if the SAP calls for an output, there had better be a shell, and if there is a shell, there had better be text in the SAP about that shell. 2️⃣ Stand on the shoulders of giants - Very rarely have I created shells truly from scratch. I am more times than not creating shells from a template my company or the sponsor has, OR I am finding results/looking up other studies that have presented results similar to the type of results I plan on presenting - if you don't have a shell for what MMRM output should look like you can always go to clin trials dot gov and search for studies that have their statistical analysis plans or results available and see if there are any examples included (if not directly available from clintrials you can see if the drug was approved, and if it was, check out it's SBA on the FDA's website for the results and some inspiration). 3️⃣ Take your time - Often (for one reason or another) you may find yourself with a tight timeline to create TLF shells. If you have any doubts that you do not have enough time to create the shells - speak with your manager as early as possible. The shells are CRITICAL for the success of the study analysis and if you rush through them you run the risk of the programming team getting stuck because the shells are not clear, or worse, you may end up creating a shell that cannot be used by the CSR development team. 4️⃣ If ever you are not sure what to include in a shell - include as much as you can - even if it is overkill. It is much simpler to remove something than it is to add something later in the game. Shells are a huge topic and one that deserves more time to be covered - if you have any questions about creating them please feel free to send me a direct message. Happy Monday

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