How to Utilize Tableau Features

If I were to start learning Tableau today, this is the roadmap I would follow ⬇ 1. Solidify the fundamentals a) Understand qualitative and quantitative types of data b) Understand dimensions and measures c) Understand rows and columns shelves d) Understand marks card 2. Creating the charts a) Create the basic charts - line, bar, pie, area, etc. b) Create charts using dual-axis - donut, combination, area with line, etc. c) Understand the use case and usability of each chart - refer to Visual Vocabulary by Financial Times 3. Getting into basic interactivity - Part I a) Understand filters, sets, hierarchy, and groups b) Create the above using use cases with knowledge of charts 4. Getting into calculations - Part I a) Start with basic calculations like sum, difference, multiplication b) Understand row level and aggregate calculation [ A must to understand] c) Create logical calculations using IF-THEN-ELSE statements b) Create boolean calculations using logical operators like OR, AND, IN 5. Getting into advanced interactivity a) Create parameters b) Understand with use cases to apply parameters to switch, sort dimensions or measures c) Understand set actions d) Understand parameter action - very powerful in terms of interactivity BEFORE YOU MOVE AHEAD, understand the order of operations and its application [ Can't miss if you want to be good with Tableau] 6. Master calculations a) Understand and create LOD calculations b) Understand the table calculations Remember the steps defined in this post for a better comprehension of the dashboarding process - https://lnkd.in/gWVzdYEJ 7. On our way to dashboards a) Master containers - Refer to Videos by Andy Kriebel on Youtube b) Understand the role of padding and how to apply them c) Understand the use of blanks for creating lines and dividers d) Understand the use of colors for dashboards—This is a tough subject, but reading Tableau's whitepapers on Data Visualization best practices will help. e) Refer to UI and UX best practices to understand the flow of placing charts, navigation buttons, and filters f) Learn advanced new features like Dynamic Zone Visibility This whole process will solidify your 1st step in becoming a good analyst with Tableau capabilities. Comment and let me know if you relate to the process and what more you would add to it for someone starting Tableau. Happy Wednesday!

No Power BI? No Problem. Everyone seems to be building dashboards in Power BI these days. But what if you don’t have access? Maybe your company hasn’t provided a license. Maybe your laptop can’t handle it. Or maybe you’re just not sure where to begin. Here’s what most people don’t realize: You can still build solid analytics skills using free, accessible tools, and those same skills will carry over when you do start using Power BI. Tools like Tableau Public, Looker Studio, Google Sheets, and Excel Online can teach you how to clean data, build dashboards, apply formulas, and tell compelling stories with data. You don’t need expensive software to start. You just need the right mindset and resources. I’ve pulled together some of the best tutorials and practice tools to help you get started: ↳ Access the Tableau Free desktop version here: https://lnkd.in/dxXxzR_m ↳ Learn how to install it here: https://lnkd.in/dkYHrQfC ↳ Introduction to Tableau: https://lnkd.in/deXZiDjG ↳ Connecting to Data Sources: https://lnkd.in/dq8ibppR Core Skills ↳ Calculated Fields: https://lnkd.in/dEdhYjYC ↳ Filters & Parameters: https://lnkd.in/dJPaGJ_i ↳ Tableau Zen Master Tips & Tricks: https://lnkd.in/dXqY3yPs ↳ Top 10 Tableau Dashboard Design Tips: https://lnkd.in/dZcewx7i Advanced Techniques ↳ Create a Stunning Advanced Dashboard in Tableau: ↳ LOD Expressions: https://lnkd.in/dSfjmuWg ↳ Tableau Prep: https://lnkd.in/dkYHrQfC Real-World Applications ↳ Tableau Public Portfolio: https://lnkd.in/dxXxzR_m ↳ Case Studies: https://lnkd.in/d_jRSttk Additional Resources ↳ Practice Datasets: https://lnkd.in/dEwcEiVq ↳ Cheat Sheets: https://shorturl.at/3SHnK ↳ Communities: https://lnkd.in/dqTZySvW Know someone who needs this? Share it with them. ♻ If you’re serious about leveling up your data career, join my WhatsApp channel for direct insights & updates, or subscribe to my YouTube channel for in-depth tutorials. ↳ My WhatsApp channel: https://lnkd.in/dawGfYjq ↳ My YouTube channel: https://lnkd.in/deiQF4DW

Percentages with variance arrows. Revenue shown in millions. Hide Zero values. When I build out views or dashboards in Tableau, I ask how stakeholders want their values, As it influences my approach. You could build calculated fields for each request. Or you could use formatting that's already there. Tableau can handle number formats without touching calculations: 1. Native formatting for basic prefixes and suffixes Right-click your measure → Format → Numbers. This handles most standard requests. Currency displays (£, $, €). Percentage symbols. Thousands separators. Decimal precision. Takes seconds and keeps your workbook clean. 2. Custom formatting for unique requests Format → Numbers → Custom. Adds symbols to positive or negative values ▲0.0%;▼0.0%;►0.0% → ▲5.2%, ▼2.1%, ►0.0% Prevents 0 from appearing #,##0;-#,##0;"" → 1,234, -567, 0 → 1,234, -567 The native formatting does have its limitations, which is when I resort to calculated fields 3. Calculated fields for dynamic scaling That's when you can build a calculation to handle your number range 750 → 750, 5,400 → 5.4K, 125,000 → 125K, 2,350,000 → 2.35M If your team's been building calculated fields for every formatting request, this might save you some time.

Day 4 of Tableau Data Cleaning Made Easy in Tableau – Visualizing the Prep Process! As I continue my Tableau learning journey, I’ve been diving into some of the most essential features for cleaning and preparing data before building any dashboards. Tableau has powerful built-in tools that help turn messy raw data into clean, structured tables — without needing external tools! Here’s what I learned and practiced: 🔹 1. Data Interpreter (Part 1 & 2): When importing Excel files, Tableau’s Data Interpreter scans your sheet and automatically removes extra header rows, formatting issues, and irrelevant notes. ✅ It’s a game-changer for cleaning up messy reports or exported files. 📸 Screenshot 1 – Original Data 📸 Screenshot 2 – After Data Interpreter applied 🔹 2. Pivoting Data: Sometimes your dataset is wide instead of long — for example, with time periods or categories spread across columns. Pivoting helps you flip columns into rows for better analysis. ✅ Essential for survey-style data or period-based reports. 📸 Screenshot 3 – Pivot applied to reshape the data 🔹 3. Splitting Columns (Standard & Custom): Columns often contain multiple pieces of data, like full names or combined address fields.Tableau’s Split and Custom Split features let you break these down based on delimiters or patterns. ✅ I used this to extract city, state, and zip from address fields — making filtering and analysis much easier. 📸Screenshot 4 – Splitting address columns using Custom Split 🎯 These steps reminded me that data visualization begins with clean data. These tools also help handle null values, structural issues, and formatting inconsistencies all within Tableau itself. #Tableau #DataCleaning #Pivoting #DataPreparation #SplitColumns #Analytics #TableauTips #LearningJourney #BusinessIntelligence #DataWrangling #DataVisualization

Do you want to learn how to swap worksheets with Dynamic Zone Visibility in #Tableau? Here are the steps you need: •Create a parameter with the worksheet options •Create boolean (T/F) calculations for each worksheet option referencing the parameter (e.g. [Parameter] = "Option A") •Add all worksheets into a vertical layout container in a dashboard •In the dashboard, select a worksheet, select the Layout menu, hit the "Control visibility using value" checkbox and choose the applicable T/F calculation •Repeat the above steps for each worksheet (and related objects like color legends if desired). Here are a few benefits of this approach vs. the old-school parameter filter swapping approach: •No Worksheet Limit: I just built a client dashboard where we could swap between 30 worksheets (not generally recommended!). The old-school method gets wonky after 3 sheets. •No Padding Issues: The old-school method always leaves a 5-10 pixel blank space even after a worksheet was swapped away from. DZV doesn't! •Titles Swap Too: Yep, worksheet titles swap out with DZV. •Can Swap Related Objects: Color legends, filters, parameters, etc. can also be swapped with Dynamic Zone Visibility Want to learn from one of the best to ever do it? Check out Oliver's video here: https://lnkd.in/gCYbTvH6

Awesome how Tableau Data Blending helps you combine data without heavy modeling. Not every dataset lives in the same place. And not every team has time to fully model everything before building dashboards. Tableau Data Blending is designed for those moments. It lets you combine data from different sources directly in Tableau, without needing to join everything at the database level. You can relate datasets on the fly and start analyzing immediately. Why teams still use it: - It speeds up analysis when data lives across multiple systems. - avoids waiting on full data modeling or engineering work. - works well for quick comparisons and exploratory analysis. - allows analysts to move forward without changing underlying data structures. It’s especially useful when working with spreadsheets, external data, or combining warehouse data with local files. It is not meant to replace proper data modeling, but it is a powerful option when speed matters more than perfection.