Jordan Hartley

🧰 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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🤔 How many times have you reinvented the wheel in Tableau?   I thought the radial jittering in my IronViz qualifier was pretty cool.   But it looks like my IronViz mentor, Samuel Parsons, had done the same thing 5 years prior.   At least I settled on the same chart name as he did, so that's what it is - a radial jitter.   These are good for infographics showing a distribution that concentrates around a central point.   📝 In the near future, I hope to make a simple dashboard showing three variations of this chart type, including evenly distributed dots as well as dots on the periphery.   In this #makeovermonday case, I thought the idea of concentrated dots meshed well with firearms - I got the idea from seeing the bee swarms by Shangruff Raina and Sherzodbek I.   Anyhow, I adjusted the worksheet size so that the output is slightly elliptical to fit well in the target image.   ⚖️ I thought I'd go down the route of comparison to domestic purchases because I knew those numbers were high. They've been higher than 2022, but I used that year because it was the last year of the other range and I wanted something semi-current.   🏗→🧠 Build to Learn!   💭🚶‍♀️🚶‍♂️ Follow for more.   #makeovermonday #tableau #data #analytics #VizoftheRay

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🤔 How many times have you reinvented the wheel in Tableau?   🦚 I thought the radial jittering in my IronViz qualifier was pretty cool.   😲 But it looks like my IronViz mentor, Samuel Parsons, had done the same thing 5 years prior.   🤷 At least I settled on the same chart name as he did, so that's what it is - a radial jitter.   These are good for infographics showing a distribution that concentrates around a central point.   🛠️ I made another simple dashboard showing three variations of this chart type, including evenly distributed dots as well as dots on the periphery.   In this makeovermonday case, I thought the idea of concentrated dots meshed well with firearms - I got the idea from seeing the bee swarms by Shangruff Raina and Sherzodbek Ibragimov.   Anyhow, I adjusted the worksheet size so that the output is slightly elliptical to fit well in the target image.   ⚖️ I thought I'd go down the route of comparison to domestic purchases because I knew those numbers were high. They've been higher in the past than in 2022, but I used that year because it was the last year of the other range and I wanted something semi-current.   🏈 This is a Throwback Thursday viz!   🏗→🧠 Build to Learn!   💭🚶‍♀️🚶‍♂️ Follow for more.   #tableau #data #analytics #VizoftheRay

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🤔 Have you ever heard of a Ziggurat Chart or a Chichen Itza Chart?   📖 It's not really a recognized thing…   I made it as a gag to tease fellow tableau developer who had recently made waffle charts and plum pudding charts.   I figured, why not try a Triangle?   🤪 It doesn't really work that well, but it *does* have 100 squares, and it's a weird way to show a percentage.   🏈 This is a Throwback Thursday viz!   🏗→🧠 Build to Learn!   💭🚶‍♀️🚶‍♂️ Follow for more.   #tableau #data #analytics #VizoftheRay

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Mike and I will land in San Diego tomorrow to represent Swift Insights at Tableau Conference this week! If you are going to be there looking for: 1. Help with your business data 2. Fully remote job opportunities 3. Or just want to hang out and talk data Let's connect at #data24!

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I’ve been getting recruiting messages again, which suggests the data job market is maybe not as bad right now as it was six months ago (but probably still bad). Some of these messages are for contract work. But some of those include job descriptions for, say, a six-month senior or principal data scientist contract where the job description reads like a vague outline of the job function itself. If you’re going to try and hire a senior member of a data team for only a six-month contract, you might recruit better candidates if you actually described the six-month project the person would be working on. Doesn’t have to give away any secret sauce. But does need to help someone understand what they’re getting into. Because if it’s a vague data science job with no direction from leadership that lasts only six months, the employer will be wasting money and the contractor will be wasting time. Kinda like how too many employers and employees have been doing with data science jobs for like ten years now, except with the added stress of no job security for the worker, and a tight timeline to complete… what exactly? If you’re gonna hire highly skilled people, why not give them a hint as to why you need their skills?

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Relying on job boards to build your dream team? Think again… Why? Recently, I spoke with the Head of Talent Acquisition for an aerospace company. Notably, they’re the only one handling recruiting and bragged about only using job boards. As we dug deeper… The real problems emerged… The company is missing milestones. Losing investor funding. And, cutting staff. This is the trap of relying solely on job boards. A-players aren’t actively looking… They’re thriving in their current roles. It’s often C-players who are on the hunt every 12-18 months. When a company builds its team mainly from job boards… They’re setting themselves up for average results. Strategically, this builds a status-quo culture that won’t keep top talent engaged. And, the cost? High turnover and damaged credibility in the talent marketplace. Oh, and the cost of having to rehire & onboard, which is 2-3 times a candidate’s salary. If your hiring strategy is built around who’s actively looking… You’re likely missing out on who you need to take the organization to the next level and we should probably explore synergies. PS Now, my Team is confidently representing their Head of Business Development and actively engaging their employees #Aerospace #Defense #Recruiting

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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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👀 I've been looking into Data Stories in Tableau.   🪙 There is some definitely some useful functionality there.   However, in that process, I got the screen below.   Do you know what I thought?   "Where the heck is the More Options context menu?!"   I don't think I ever even read the "More Options" hint on the dropdown arrow (aka caret, aka "disclosure triangle", aka "menu indicator") on dashboard objects. Has that always been there?   Anyhow, I eventually figured it out.   And if you didn't know, now you do!   🏗→🧠 Build to Learn!   💭🚶‍♀️🚶‍♂️ Follow for more.   #tableau #data #analytics #VizoftheRay

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One thing I love about Analytics: data shows up everywhere in the world around us. And if you're a curious Data Analyst you probably even have a "data hobby" - something outside your profession or industry - that you get excited to learn about - even if it's just for fun For me, it's baseball analytics. I've played the game since I was 5 years old and I always dreamed of playing professionally. That dream didn't come true 🤣 But nowadays, I get plenty of enjoyment thinking about all of the decisions being driven by Data Analysts working in the baseball industry. - advanced models estimating player value - event probabilities driving in-game decisions - cloud integrations harnessing real-time analytics As a fan of Baseball and a fan of Analytics, it's the purest data hobby I have. What's yours? #data #analytics #baseball #curiosity

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❓ 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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There are 31,966 job with "Tableau" in the title on LinkedIn...RIGHT NOW! But wait... Are you ready to take advantage?  While the demand for Tableau skills is through the roof, the number of qualified candidates remains scarce. Here's a breakdown of a just a few markets in desperate need:  USA: 27,797 jobs   • New York: 3,786 • San Francisco: 3,164 UK: 4,169 • London: 2,142 Almost half of the open jobs offer some sort of remote working. 𝗧𝗵𝗲 𝗣𝗿𝗼𝗯𝗹𝗲𝗺?   While the jobs are plentiful, quality training to equip you with the skills you need is limited. This creates a massive gap between companies needing experts and individuals ready to fill those roles. 𝗧𝗵𝗮𝘁'𝘀 𝘄𝗵𝗲𝗿𝗲 "𝗡𝗲𝘅𝘁-𝗟𝗲𝘃𝗲𝗹 𝗧𝗮𝗯𝗹𝗲𝗮𝘂" 𝗰𝗼𝗺𝗲𝘀 𝗶𝗻!   My comprehensive training program will transform you from a Tableau novice to an expert. It's the only training program in the world that offers live and on-demand training. Here's what you'll gain: - 𝗠𝗮𝘀𝘁𝗲𝗿 𝘁𝗵𝗲 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀:  Build a solid foundation in Tableau functionalities and best practices. - 𝗖𝗿𝗮𝗳𝘁 𝗰𝗼𝗺𝗽𝗲𝗹𝗹𝗶𝗻𝗴 𝘃𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝘀: Learn to create impactful dashboards and analysis that tell a clear story. - 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝘁𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀:  Unlock the full potential of Tableau with advanced features and data manipulation. - 𝗖𝗮𝗿𝗲𝗲𝗿-𝗿𝗲𝗮𝗱𝘆 𝘀𝗸𝗶𝗹𝗹𝘀:  Gain the expertise employers are actively seeking. Don't miss out on the booming Tableau job market! By enrolling in Next-Level Tableau today, you'll be one step closer to becoming the Tableau expert companies are desperately searching for. DM me "practice" and I'll give answer all of your questions to see if NLT is right for you. 𝗧𝗛𝗔𝗧'𝗦 𝗡𝗢𝗧 𝗔𝗟𝗟! Sign up for an annual subscription in May and you get 1 free hour of 1-to-1 training with me ($1000 value).

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Some tough conversations this week, but with that I'd like to reach out to my network here! I know of some folks in an analytics role that were recently impacted by business decisions. I want to help them land in another spot and could use your help! If you know of a role where skills in SQL or general data tools are needed with an aptitude towards learning newer tools, please let me know in a message, I'd love to chat!

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🤔 How can you outperform some of the best Tableau developers?   📝 Update the tooltip in your show/hide button so it doesn't say "Show 'Vertical' "!   Yes, I've seen that on dashboards on Tableau Public made by even the best Tableau developers.   They're human; they make mistakes and have omissions just like you do.   Or maybe they didn't think updating it was relevant or important to what they were showing.   But it *is* relevant to your business users.   You can put whatever name you want in those quotes in two different ways.   1. (Default) It's the name of the dashboard object that you are hiding/showing.   Follow these steps: ✔ Right-click that object in the Layout tab ✔ Select "Rename Dashboard Item…" ✔ Type in a better name, like Filters or whatever is in that floating sheet.   HOWEVER, I don't even like those quotes. I think they look clunky.   2. Click the button and its dropdown, and select Edit Button. In the Tooltip field at the bottom for both modes (Item Shown/Item Hidden), you can type any prompt you want, like: ✔ Show Filters ✔ Hide Filters   I hope that makes your dashboards a teensy bit better in the UX department. 👍   🏗→🧠 Build to Learn!   💭🚶‍♀️🚶‍♂️ Follow for more.   #tableau #data #analytics #VizoftheRay

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❓ Did you know that Tableau's character sort is case-insensitive?   ⚖️ That means that it treats capital letters and lowercase letters as the same.   👍 That's probably a good thing and a useful default.   😀 The (somewhat funny) problem that I ran into is that has my RDBMS (Teradata) has case-sensitive sorting.   📃Capital letters sort first, lower case letters later.   ❌ I was testing my dashboard with some queries against the source data and many of my metrics were off for the first row.   🔍 In the Teradata tool, the text fields were also being truncated for display as in the "Output" section of the image.   👁️ So initially, I couldn't see the sort disparity.   👍Once I saw it, I wrapped my ORDER BY with an UPPER(variable), which eased the comparison, and everything was fine.   📝 Sometimes it's the little things (assumptions) that cause problems.   🏗→🧠 Build to Learn!   💭🚶‍♀️🚶‍♂️ Follow for more.   #data #datascience #analytics #VizoftheRay

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Hey, Gil Gerstl, here are some thoughts. 1. There is evidence that large labor market actors can influence other employer decisions, such as voluntary minimum wages, so I would expect Amazon's decision to influence return-to-office policy decisions in aggregate, although I don't know to what extent. See Derenoncourt et al.: https://lnkd.in/gB2ajgqQ 2. Very important question to ask is: How much does the impact of return-to-office policy on attrition risk depend on worker performance? I bet the difference is small and hard to distinguish from the noise that arises from error in performance measurement, which is very very high for corporate office jobs. So companies looking to shed headcount using return-to-office policy (which I suspect is part of Amazon's motivation) probably aren't too afraid of their average performance dropping too much if they use this as a means to increase unregretted attrition. And if some of their absolutely crucial employees might leave because of it, I bet they'll find some way to flex the policy for those key employees. 3. If return-to-office policy changes have similar effects on attrition risk regardless of performance, the question is about how the policy will affect BASELINE attrition risk. If a company thinks that their return-to-office policy will cause a baseline risk shift so large that they overshoot their workforce reduction goals, they will find ways to make that policy more lenient, or find exceptions. I bet they will overshoot their workforce reduction goals a bit, though, because workforce management decisions are usually behind the curve, especially in large bureaucracies. Then when the labor market turns toward the supply-side, employers will be slow to act there, as well, and (as they were during the pandemic and are possibly doing now) possibly over-react. 4. The impact of return-to-office policy likely varies by job function, and that is easier to measure than how it varies by worker performance. I'd encourage employers to do what they can (surveys, experiments, pseudo-experiments, just thinking about it from first principles) to measure how the impact on attrition risk might vary by job function, department, etc. Then they can see where and to what extent return-to-office policy will impact the operations of specific departments and other groupings of workers, and how that should influence the way their policy affects different workers. Of course, there are many reasons you have to be careful about that, some relating to employer brand, and others possibly to legal ramifications (and I am not a lawyer so won't speak to the latter).

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SHRM Update: The Differences Between HR Business Partners and HR Generalists! 😊 We typically find true-to-form HRBPs working at major corporations and organizations with the scale to execute a shared services HR model. As a business-facing and strategic-oriented job, they serve as more of a consultant to the company, offering the most pertinent personnel solutions while serving in an advisory capacity (alongside business executives and managers). On the other hand, HR generalists have end-to-end contact with every aspect of HR. They are typically found in smaller/medium-sized organizations and serve everyone there in a more hands-on way. While an HR generalist can function strategically, much like an HRBP, they are more operations-focused and take on daily tasks. An HR Generalist, for instance, would typically handle a problematic employee matter from beginning to end and complete the inquiry. Still, an HRBP would only become involved indirectly and instead rely on a specialized Employee Relations team to take appropriate action. Along with that, the 'hybrid' model is becoming more prevalent. People in these hybrid roles typically receive far more support than a genuine HR Generalist while still being accountable for everything under operational responsibility. Although jobs like this one are frequently referred to as HRBPs, they are typically found in organizations trying to transition but have not yet created the proper structures to support an HRBP in its purest form.

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