Thais Cooke

❓ Have you ever wanted nulls in Tableau histogram bins on the right?   The default is on the left.   In my use case, that didn't make sense.   I am showing the count of days of delay between two events.   So time increases to the right.   To me, it makes sense for the events that never completed (null) to appear on the far right - beyond the longest delay for something that actually happened, not before the earliest events.   One way to do this is to: ✔️Create a calculated field converting that null to a value greater than your biggest bin. Like: IFNULL([Days Delayed],99) ✔️Make that a discrete dimension ✔️Put it to the left of your bin pill so it sorts first ✔️Un-show headers ✔️Clean up formatting (like alias the null to "Never")   You can see the progression in the workbook link in the comments:   🏗→🧠 Build to Learn!   💭🚶‍♀️🚶‍♂️ Follow for more.   #tableau #data #analytics #VizoftheRay

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Your Data Science Lab data snack this week is all about crosstables with the {janitor} package. Try out how straightforward this package is for generating complex crosstables with counts, percentages, and more. It all runs in your browser, no installs needed. #rstats #datascience #dasl https://lnkd.in/g-Pr-Bij

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Simple guildlines to start your project! After that you can add to your portfolio/linkedin articles!

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My SQL Journey: Exploring JSON and Spatial Data Types 🚀 As I continue my journey in SQL, I’ve recently dived into two fascinating data types: JSON and Spatial. Both of these are new to me, but they’ve quickly become essential tools in my data toolkit. Here’s a glimpse into what I’ve learned so far: 🌐 JSON Data Type JSON (JavaScript Object Notation) is a flexible data format that’s perfect for storing structured data in a readable and lightweight way. It’s enclosed in curly braces {}, where data is stored as key-value pairs, separated by colons :. JSON is ideal for handling semi-structured data, making it great for APIs, configurations, and more. 🌍 Spatial Data Type Spatial data types are used to represent geographic and geometric data, like locations, routes, and areas. Common types include POINT for single locations, LINESTRING for connected points (like roads), and POLYGON for areas (like boundaries). Spatial data is crucial for GIS applications, location-based services, and mapping, allowing for complex queries like distance calculations and boundary checks. Why I’m Excited About These Data Types Both JSON and Spatial data types open up new possibilities in database management and data analysis. Whether it’s organizing semi-structured data or working with geographical information, these data types are incredibly powerful. A Special Thank You I’d like to extend a heartfelt thank you to Dhaval Patel Sir, Hemanand Vadivel Sir, and the entire Codebasics team. Your guidance and support have made this journey more insightful and rewarding. I’m grateful for your dedication and for making this learning experience so enriching. I’m eager to continue exploring these topics and see how they can be applied in real-world projects. If you have any tips, resources, or experiences to share about JSON or Spatial data types, I’d love to hear them! #SQL #Learningjourney

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🧰 There are some standard practices you should have in your toolbox when working in Tableau.   ✔️ For example, of you are going to perform major surgery on a sheet, duplicate it first.   ✔️Likewise for calculated fields.   🔒 Do this because you want to keep a working copy around. Yes, you can back up the entire workbook, but you may have other changes in there that you want to keep.   🪙 Anyhow…   🔧 Another tool in the toolbox is brute force filter removal.   💾 For this, you want to save your workbook first because you are going to discard your changes after you're done with this one, and I'll explain why at the end.   🔎 Many times in analytics, your actual problem is one of filtering. If you suspect this to be the case, then read on.   📷 The image shows the number of filters I had on this sheet. Yes, it's a lot.   🌎 If you operate in the world of healthcare data and have convinced users to have 3 or fewer filters, by all means, enlighten me in the comments as to how to achieve that.   🧙 So, my Viz-in-Tooltip was returning no results (bonus tip: I put "VIT" in the worksheet name of all such sheets) . After A TON of fooling with filter parameters and online searches and videos, I finally channeled my inner virtual manager, Sandy. The real Sandy is quite amazing - she is both wise and powerful (to borrow an LOTR quote - but otherwise, she is unlike Saruman…), but she was out of the office at the time.   🔮 Inner Sandy told me to remove the filters one at a time until my data reappeared. (IRL Sandy had advised me to do this on a prior occasion).   🏆 This indeed revealed what the problem was. I was falsely assuming that two of the filters had no negative effects. (What did I post about assumptions and bugs?)   📝 The reason that I then just discarded changes is that because removing some filters (like those for All sheets using the data source) screws up all your other sheets. It's easier to just hack away, discard, and reopen. Yes, I *could* carefully remove and reinstate them, but that takes too much time and effort.    🏗→🧠 Build to Learn!   💭🚶‍♀️🚶‍♂️ Follow for more.   #data #datascience #analytics #VizoftheRay

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This week I'll be sharing my 3-step approach to clinical analyses, starting off with exploratory data Analyses. 𝗘𝘅𝗽𝗹𝗼𝗿𝗲 ➡ Assess ➡ Validate Start off any project with an exploratory data analysis. This is when you familiarize yourself with the data layout, the meaning of each data element, and their distribution. This helps you find missing or erroneous data, outliers, and data that should be cleaned prior to the assessment. 𝗟𝗲𝗮𝗿𝗻 𝗣𝗵𝗮𝗿𝗺𝗮𝗰𝘆 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗢𝗻-𝗱𝗲𝗺𝗮𝗻𝗱 Check out https://lnkd.in/eiC92Bfk for guided lessons and projects analyzing pharmacy data in Excel. ______________________________________ Disclaimer: The views expressed are those of the author and Sparx Analytics LLC and may not represent those of any other affiliation.

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Have you seen this? I just tried it out this morning and it's pretty slick for spinning up a PBI report without leaving Jupyter Notebooks. I have a pro license and executed it in my personal Jupyter Notebook (not on Fabric). I have heard it does work on the trial licenses and in #Databricks. You can even push reports into workspaces for further use, collaboration, or presentation. Stay nerdy my friends! ------ Release notes: https://lnkd.in/eXUCAySG Documentation: https://lnkd.in/eU2peQqX ------ #powerbi #python #datavisualization

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Success isn’t always about big milestones. Sometimes, it’s the small wins that keep us moving forward. I remember early in my career when I was just starting out as a data analyst. My first ‘win’ wasn’t some groundbreaking insight, or a cool new report—it was figuring out how to automate a really simple report. It saved me hours each week, and while it wasn’t cool and flashy, it gave me the confidence to tackle bigger challenges. Small wins add up. They build momentum, and before you know it, they lead to those bigger, game-changing moments. Have any recent small wins? Celebrate the steps we take along the way! #SmallWins #CareerGrowth #DataAnalysis #Momentum"

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Chances are you didn't invent the database. But there are still so many ways you can use one to automate what you do. Automating makes it simpler to get things done, gives your work more credibility (you took the time to automate it, so you show that your time is valuable), and primes you and prepares you to make incremental improvements. #automation #efficiency #productivity #dataanalytics

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😱 I once made a really bad dashboard on purpose.   🏆 Then someone challenged me to explain how to fix it.   🔨 That was a lot of extra work, but I did it.   🖱️ I loaded it up with show/hide text buttons with explanations and links to external resources.   🚛 It's a truckload of data viz design knowledge in one place.   🔧 The dashboard has been adjusted after each of several presentations to university students in the U.S., Canada, and the U.K.   🏈 This is a Throwback Thursday viz!   🏗→🧠 Build to Learn!   💭🚶‍♀️🚶‍♂️ Follow for more.   #tableau #data #analytics #VizoftheRay

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Generative AI isn't just for super technical people—it can massively save time and reduce potential human error! Recently, I was organizing a Teams meeting for a group of 300+ people and needed to consolidate existing contacts from prior invites. Unfortunately, Teams didn't offer a feature to duplicate all emails from previous meetings. When I tried to bulk copy all the emails, they were formatted with random characters, making them unusable. Rather than copying each email one-by-one, and potentially misspelling some, I used ChatGPT to scrape all the emails. I copied the relevant emails and instructed ChatGPT to "return these in email format." It worked perfectly, returning all the relevant emails so they could be copied over. This allowed me to quickly create the Teams meeting with the accurate group of contacts, saving me a lot of manual time and effort! #GenerativeAI #ProductivityHacks #DigitalTransformation #TimeSavingTips #AIForEveryone

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🙏 Will you mentor me?   ❓ I get this question occasionally.   ✔️ My response is: I already consider myself to be a mentor in a different way.    ⚖️ There are two types of mentoring: active and passive.   I take a passive mentoring approach on LinkedIn.   ⌨️ I share my journey as an analytics professional and Tableau developer to help others learn.   Every author of content you read can be seen as a passive mentor.   Some of my passive mentors include The Flerlage Twins, Adrian Zinovei, Ryan Sleeper, Jeffrey Shaffer, Andy Cotgreave, Joshua Milligan, Jonathan Drummey, David Langer, Sam Parsons, Lorna Brown, Heidi Kalbe, Donabel Santos, Bethany Lyons, and many others.   Several of them I have never contacted.   🚚 There’s a wealth of knowledge available from people without needing direct interaction.   There are a couple of reasons I find it challenging to take on active mentoring: 📌 Creating content consumes most of the time I am willing to dedicate to knowledge-sharing. 📌 Many folks often need quick solutions to specific issues, which can usually be found in the Tableau Community forums. It’s often more efficient for them to get help directly.   I've seen a content creator try to mentor everyone that asked - they burnt out and don't even post anymore.   If someone is seeking a mentor via LinkedIn, below is how I would see that evolving. Feel free to adapt this to your own style: ✔Know where you’re trying to go.  It’s important to be clear about what you want to achieve. ✔Find someone who has reached those same goals. ✔ Follow them and engage with their content. Keep what resonates and let go of what doesn’t. Congratulations, you’re already on your way to being mentored! ✔ Build a connection by interacting meaningfully with their posts. Thoughtful questions or insights can lead to great conversations. Spend a few weeks doing this. ✔ After some time, send a connection request. Just remember to include a friendly message! Here’s a simple template: Hi [name], I enjoyed your post about [something] and it really helped me [do something]. It seems we have similar interests in [a list of stuff]. I’d love to connect! Best wishes, [your name]. ✨ It’s best not to mention a mentoring relationship right away.✨ ❌ Avoid sending a "cold" connection request (one without a message) followed by a quick ask for mentoring; it will create an bad first impression. ✔ Keep engaging with their posts for a while longer. ✔ Once they may recognize your name, reach out with one specific question that applies only to you. For more general questions, consider posting them in the comments instead. ✔ Based on their response, you can gauge the right timing for your next inquiry.   📝 Remember, active mentoring is about building a relationship, much like nurturing a plant. It takes time and care to grow.   🪴Happy gardening!   🏗→🧠 Build to Learn!   💭🚶‍♀️🚶‍♂️ Follow for more.   #tableau #data #analytics #VizoftheRay

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I have just submitted my reproduction of Cara Thompson's work, #BarBeRight, to the plotnine contest. Here is the link to the tutorial: https://lnkd.in/gBtktGsR Credit goes to Cara Thompson for her insightful tutorials and superb work on Data Visualization. #plotnine #datascience #rstats #python

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So I never thought I'd run into a case insensitivity issue in PowerBI, but I did today. I couldn't figure out why I had two distinct rows in my matrix table. I was able to fix the problem in SQL before I even identified what it was. To troubleshoot, I copied the SQL output to Excel, and also ran distinct values. Both times overlooked a lower case "i" in the raw data. Finally the third time I looked at SQL and I found the difference which wasn't obvious in Power BI. For some reason PowerBI capitalized the abbreviation. Afterward, I found the following article blog post by Chris Webb #PowerBi #DataAnalysis #DataAnalyst

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Imagine you have 30 SQL files to run each reporting cycle. Every month, you find yourself clicking through each one of them, waiting for it to finish running before moving on to the next. It’s not just time-consuming—it’s mind-numbing! But that was me *before*. I’ve just leveled up my workflow by using Python to automate the entire process. No more manual clicks, no more wasting time, no more boring tasks. I’m incredibly proud of this new skill and can’t wait to tackle more exciting projects with #Python.

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🪙 Here's a not-so-common SQL use case.   📄 So what I had was multiple rows for each key I was interested in.   Those rows had an ordinal field, the order of which is not the alphabetical order of the dimension values.   A row with the variable set to the "first" ordinal value might not exist, but if it does, I want the data from that row, and on down the line - second if available, third, etc.   Keep in mind, I don't actually care what the value of that ordinal field is.   I just want the row AS OF the highest ordinal value.   So this is where CASE came in handy. I've used it in ORDER BY in a main query, but never in the ORDER BY of a window function.   So the final step in this solution would be to wrap the query in a another query that selects WHERE row_num equals 1.   As an alternative, I *could* avoid that last step by using FIRST_VALUE() for every field that I want by the same PARTION and ORDER.   Anyhow, I thought it was an interesting problem.   🏗→🧠 Build to Learn!   💭🚶‍♀️🚶‍♂️ Follow for more.   #tableau #data #analytics #VizoftheRay ---- 

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New "Prosper In Data" issue is coming out tomorrow! I will be talking about my previous project that I did and how it works. It's a perfect project to have in your portfolio if you're trying to get into ML & AI! The link will be down in the comments.

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With analytics, you can do so much with just SQL and a data vis tool or excel. Great analytics really depend on 4 things: 1. How much data is available (Access) 2. How efficient you are to "clean" it (Transformation) 3. How you can make good decisions out of it (Actionable insights) 4. The right people who could drive the actions (Stakeholders) Without access, you just have tools with nothing or very little to analyse. Without efficient transformation, you'd probably go insane with all the garbage and noisy data. Without actionable insights, you just have a "sexy" nice-to-have dashboard Without proper stakeholders, the analysts would probably just be staring at each other 😂 #HealthAnalytics #Intelligence #Analytics

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Career Conundrum: Higher Pay vs. Better Job Satisfaction My fellow data professionals, would you rather: 💰 Option 1: Chase the dollars with higher pay at an "okay" job? 💡 Option 2: Prioritize satisfaction in a role aligned with your passions, even with okay pay? Each has trade-offs, and no one option is better than the other. Any out-of-the-box ideas to rethink the question? 🤔 💬 Share your thoughts or suggest a third path in the comments! Your input is invaluable 🙏 #CareerInsights #JobDilemma #DataAnalyticsDreams

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