Daniel Cole

For current or aspiring independent data consultants, are you struggling to grow your practice? Would $1M+ in revenue in 12 months be compelling? I'm considering putting together a course on how I did just that. DM me if this would be of value.

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Let's be honest BI developer may create a great dashboard but many suck at Data storytelling Q3 revenue in column B (or point to the chart) and growth percentage in column C This is not a story, analytics people focus on facts, data accuracy than being relatable. For starters this is better In Q3, we increased revenue by 35%, outperforming our last two quarters, thanks to targeted campaigns that helped to drive revenue up. What are the worst or boring data stories you have heard?

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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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📊😂Just spent an hour staring at my screen, trying to remember why I opened this spreadsheet in the first place. Ah, the joys of data analysis! 💻🤷‍♂️ I often find solace with pivot tables. Even after mastering multiple scripting languages, there's something oddly comforting about their simplicity😌 #DataChaos #AnalyticsHumor #dataanalysis #googlesheets #Datazen #pivottables

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If you've ever tried to join two tables in your #DataModel in either #Excel #PowerPivot or #PowerBI, and been blocked by 🤚 or warned about duplicate values, a bridge table may be just what you need. In this video, I shows my preferred recipe for creating bridge tables, ensuring that you'll never have an orphaned record in your end results. 👍 Watch here: https://lnkd.in/gME3qUHG

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The best analytics leaders I've worked with are masters of managing up. They keep executives informed while shielding their teams from distractions. A valuable skill to learn.

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Machine Learning Week conference is in Phoenix, AZ this week where the forecast is 110+. Now we all know correlation does not mean causation, but when it comes to AI & ML this conference really brings the heat! Come join the fun! #machinelearningweek #aiplaybook

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🙃 This is a weird Tableau use case…   ✔️ but it happened.   I wanted to move a single Dimension value from the Other group (that was generated when I checked "Include 'Other' ") to its own group.   The image with Superstore data is analogous to my real world problem.   I went down a rabbit hole of thinking about this the wrong way.   If you right-click, and choose Add to…, well, the Group doesn't exist yet and you're sunk.   Don't do what I eventually came up with: ❌ Ungroup all Other items. ❌ Make the single item a Group. ❌ Re-check Include Other.   Instead, just select your single item from Other and click Group.   You can re-group from existing groups like that - occasionally useful.   🏗→🧠 Build to Learn!   💭🚶‍♀️🚶‍♂️ Follow for more.   #tableau #data #analytics #VizoftheRay

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Only a fraction of businesses use Generative BI. Use it to transform your operations. Why Generative BI? It's your secret weapon. It's a game-changer. It makes data simple. It makes decisions smart. ✓ Start with one data source: Get going without overthinking. ✓ Break the norms: Traditional tools fall short. AI is the future. ✓ Solve real problems: Overcome data overload and integration issues. ✓ What it does: Simplify tasks, drive decisions, ensure security. ✓ Embrace the future: Consistent use leads to breakthroughs. Use Generative BI to: • Simplify complex BI tasks. Make them easy. • Drive meaningful decisions. Ask natural language questions. • Maintain data privacy. Keep it secure. • Democratize data access. Share it with your team. • Gain competitive advantages. Stay ahead. Ready to transform your business? Integrate Generative BI thoughtfully. Understand, apply, and lead with innovation. As technology evolves, so should your business. Now take the lead. Be innovative. Be exceptional. Have you integrated Generative BI?

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PowerBI or Tableau Unicorn🦄 or Dragon🐲 📌Do you sometimes get caught up in things you can't control?➡️Messy dataset 🎯What if we channeled that energy towards what we can control?➡️Mindset filter This simple #focusonwhatmatters mindset shift can lead to better outcomes. ⁉️What’s one uncontrollable aspect you’re ready to let go of? #TeamBayer #MindsetShift #powerbi #thoughtleadership

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When working in #PowerQuery in #Excel, you can choose various load destinations for your queries. When you mouse over the preview pane, you’re either told that the query loads to Connection Only, or as “x Rows Loaded”. But it doesn’t tell you WHERE they’ve been loaded. Well guess what? Destination Sleuth knows! 💥 Learn more at mkyt.ca/destsleuth

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FREE LIVE TRAINING CLASS! The Data Visualization Checklist Wednesday October 2 at 2pm Eastern Wouldn’t it be so nice to have a set of guidelines that tells you exactly how to format your chart so that your story shines through? Yeah, thought so. That’s this class. Come get some (free!) training on this (free!) tool that will sharpen your charts. I expect the training to last an hour, but we often have so much audience engagement that it’s hard to say for sure. So, bring your thoughts and questions. Bring your own chart to rate with the Checklist. Yes, I’ll record the class and send out the recording to everyone registered but it’s never as fun as it is live. Hope you can make it. 

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Want to ditch data analysis confusion & become a rockstar? Our latest post defines reproducibility & shows you how to document your work for clear, repeatable results. https://wix.to/kEpcU5r #newblogpost #DataScience #Reproducibility #dataanalystskills #analytics

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I've written before that titles are meaningless in data and all that matters is your capabilities. Here's a deeper explanation... I've been a VP with zero reports. I've been a Director with 100 data people reporting to me while owning the P&L of a nine-figure data business. "Lower" title, but way more actual responsibility. There are people who get a senior data title after 12 months of work experience. I know a "Senior Manager" who ran data strategy at a >$50 billion company, after previously leading data strategy at a >$100 billion company. And countless other examples... This is why in data, anyone competent will calibrate your seniority based on your actual capabilities, achievements and impact - not based on your title.

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Too Late II Many national retailers have a singular focus. Beat last year. To that end, tools like Power BI are used to chase metrics like never before Some companies go to the extreme, chasing metrics they didn't even know existed 5 years ago Other companies are narrowing their focus, abandoning accessory add ons in favor of selling more of their core product Regardless of the approach, these hamster wheel strategies are doomed to failure Beating last year means more of everything this year. More customers, More UPTs, a higher average ticket, a higher conversion rate Stretch goals were created for this strategy. You must be better this year in order to beat last year, every year Your plan to beat last year this year needed to be implemented last year in order to beat last year this year Got that? Let me put it another way You grow your business on who comes back tomorrow, not on what you sell today In fact, fixating on metrics to be better than last year is a form of Food Poisoning that drives the customer away You think the customer doesn't feel that extra push? More importantly, you think they don't remember that extra pressure? They never forget it Which is why companies focusing on beating last year this year are struggling to beat last year this year Companies need to focus on beating next year this year, a concept that escapes most, but not Unified Leadership Theory (ULT) The Third Law of Customer Loyalty The customer is only as loyal as their last transaction You must treat every transaction like you will never see the customer again if you don't handle their situation correctly We already have a baseline. What makes me mad makes you mad. What makes you happy makes me happy We are not that complicated Make customers happy. If it would piss you off, don't do it This is how you capture the customer that quietly walks away. They don't complain. They don't make a scene. They don't forget. They don't come back It's not just customer service. Adding more and more to your employees’ plates only disengages them further Employees know they are disengaged. Customers sense it Your employees don't want empathy. Your employees want action What are you doing to allow us to focus on the customer experience so the customer wants to return next year??? You must have a complete strategy Employee Engagement Customer Service Efficiency All of it You must be better this year than last year in order to be better next year than you were this year I can't make it any more clear than that d;0) Unified Leadership The Strategy of Engagement

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User buy-ins are most important!!!! In my experience, whether it's business intelligence or any IT solution, you need to get buy-in from end users. Many organizations face resistance from subject matter experts accustomed to using tools like Excel for data analysis. These experts are often protective of their custom dashboards and reports, making it challenging to introduce centralized BI solutions. However, overcoming this challenge requires a delicate balance of appreciation and education. In situations like this, I try to show them how the knowledge they aggregate can benefit multiple areas of their organization. But before we can do that we must acknowledge the expertise of these individuals. Only then can we demonstrate the benefits of adopting modern BI tools. By showcasing how centralized reporting systems can enhance their existing skills and streamline data analysis processes, we can drive faster adoption. Education plays a crucial role in empowering end users to embrace change and leverage new technologies effectively. A person would be willing to overcome their resistance only if they feel that the initial hurdle of learning something new is far outweighed by the pros of adopting the tech. Once they understand the value proposition and feel confident in their abilities, the transition to BI solutions becomes smoother. Have you started using professional business analytics tools in your organization? If not, what is the biggest challenge you are facing? Let me know in the comments. #businessintelligence #dataanalysis #changemanagement

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What do we get wrong as data leaders? Predictability. Let me explain. When your business partners ask you how long it is going to take to build a dashboard, what do you say? Commonly, you'll hear a range (like 4-6 weeks). And, also commonly, something throws a wrench in this range and it has to be extended. What about when it comes to investment decisions? For how example, how much will this new data platform cost? We think it will cost $1 million, and then after implementation it was actually $1.75 million. Businesses (and business partners) crave predictability. Now the detractors will say "data is too complicated for this" or "it's impossible to forecast exactly how much investment we'll need." Guess what? I don't buy it. If large technology companies can forecast out their financials, and can set dates for product releases, why can't you? Predictability is a way that a data team will have greater credibility and more likely to be treated as another business team. The more that you can do this as a data leader, the greater success you will see. #data #dataculture

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🎉 And the results are in... 🎉The best type of Analytics Engineering job opportunity is 🥁 Last week, I posted a poll to uncover the most attractive type of Analytics Engineering role. Here's what you all had to say: 1️⃣ The first data hire — capturing the logic around the business and setting up the data foundations and stack: 37% 2️⃣ Joining an established data team with a mature stack — typically growth or replacement hires: 34% 3️⃣ Joining a data team that's new to the modern data stack or Analytics Engineering: 28% Are you surprised by these results? 🤔 I'd love to hear your thoughts in the comments! 💬 #DataAnalytics #AnalyticsEngineering #DataCareers #PollResults #DataTeam #ModernDataStack

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