[Forward: I asked ChatGPT o1-mini who then wrote this. Hope it helps. All the credit and the blame go to ChatGPT.

I went over the plan and it looked decent. Whether it can be done in 30 days or not, it depends on the person and the time he spends on it. By the way, ChatGPT can be a really good study buddy. Ask it questions whenever you have any.]

This comprehensive 30-day plan is designed to take you from a Tableau beginner to an advanced user. Each day includes specific learning tasks, recommended resources, and practical exercises to build and reinforce your Tableau skills.

Week 1: Introduction and Basic Concepts


Day 1: Introduction to Tableau


• Topics:

• Overview of Tableau and its applications.

• Differences between Tableau Desktop, Tableau Public, and Tableau Online.

• Resources:

• Tableau Official Getting Started Guide

• YouTube Video: Tableau for Beginners

• Exercise:

• Install Tableau Public (free) or Tableau Desktop (trial version).

• Explore the Tableau interface and navigate through menus and toolbars.


Day 2: Connecting to Data


• Topics:

• Types of data sources (Excel, CSV, SQL databases, etc.).

• Live vs. Extract connections.

• Resources:

• Tableau Help: Connect to Data

• YouTube Video: Connecting to Data in Tableau

• Exercise:

• Connect Tableau to multiple data sources like Excel and a sample SQL database.

• Explore and familiarize yourself with data connection options.


Day 3: Basic Data Manipulation


• Topics:

• Understanding data types and field properties.

• Renaming, sorting, filtering, and grouping data.

• Resources:

• Tableau Tutorial: Basic Data Preparation

• YouTube Video: Data Manipulation in Tableau

• Exercise:

• Use the Superstore dataset to rename fields, sort data, apply filters, and create groups.


Day 4: Creating Basic Visualizations


• Topics:

• Building bar charts, line charts, pie charts, and tables.

• Understanding Marks card and encoding data visually.

• Resources:

• Tableau Official Visualization Guide

• YouTube Video: Creating Basic Charts

• Exercise:

• Create a bar chart for sales by region, a line chart for sales over time, and a pie chart for sales by category using the Superstore dataset.


Day 5: Working with Filters


• Topics:

• Applying dimension and measure filters.

• Using quick filters and filter actions.

• Resources:

• Tableau Help: Filtering Data

• YouTube Video: Using Filters in Tableau

• Exercise:

• Apply filters to your visualizations to display sales data for specific regions or time periods.

• Create a dashboard with interactive filters.


Day 6: Aggregation and Granularity


• Topics:

• Understanding data granularity.

• Aggregation functions: SUM, AVG, COUNT, MIN, MAX.

• Resources:

• Tableau Tutorial: Understanding Aggregation

• YouTube Video: Aggregation in Tableau

• Exercise:

• Create visualizations showing total sales, average profit, and count of orders by different dimensions.


Day 7: Review and Mini Project


• Review:

• Revisit all topics covered during the week.

• Consolidate your understanding through summary notes.

• Exercise:

• Build a simple dashboard summarizing key metrics like total sales, profit, and average order size.

• Publish your dashboard to Tableau Public (if using Tableau Public) and share it.


Week 2: Intermediate Tableau Skills


Day 8: Advanced Calculated Fields


• Topics:

• Creating calculated fields using functions and formulas.

• Introduction to Level of Detail (LOD) expressions.

• Resources:

• Tableau Tutorial: Calculated Fields

• YouTube Video: Calculated Fields in Tableau

• Exercise:

• Create calculated fields for profit margin and year-to-date sales using the Superstore dataset.


Day 9: Working with Dates


• Topics:

• Date functions and custom date formats.

• Creating date hierarchies.

• Resources:

• Tableau Help: Date Functions

• YouTube Video: Date Calculations in Tableau

• Exercise:

• Analyze sales trends by creating monthly, quarterly, and yearly views.

• Calculate Year-over-Year (YoY) growth using date functions.


Day 10: Joins and Data Blending


• Topics:

• Joining multiple tables within Tableau.

• Difference between data blending and data joining.

• Resources:

• Tableau Help: Joins and Blends

• YouTube Video: Data Blending in Tableau

• Exercise:

• Join the Superstore dataset with a custom customer dataset.

• Create visualizations that combine information from both datasets.


Day 11: Parameters in Tableau


• Topics:

• Creating and using parameters.

• Parameter controls for interactive dashboards.

• Resources:

• Tableau Help: Parameters

• YouTube Video: Using Parameters in Tableau

• Exercise:

• Create a parameter to switch between different measures (e.g., Sales vs. Profit).

• Implement the parameter in a dashboard to allow dynamic data views.


Day 12: Creating Maps and Geographic Visualizations


• Topics:

• Building geographic maps using latitude and longitude.

• Custom territories and map layers.

• Resources:

• Tableau Tutorial: Creating Maps

• YouTube Video: Mapping in Tableau

• Exercise:

• Create a map showing sales by state or country.

• Enhance the map with color gradients to represent different sales volumes.


Day 13: Dual-Axis and Combination Charts


• Topics:

• Creating dual-axis charts.

• Combining different chart types for richer insights.

• Resources:

• Tableau Tutorial: Dual-Axis Charts

• YouTube Video: Dual-Axis in Tableau

• Exercise:

• Create a dual-axis chart showing sales and profit on the same graph.

• Experiment with combination charts to display multiple data dimensions.


Day 14: Review and Intermediate Project


• Review:

• Go over all intermediate topics covered during the week.

• Clarify any doubts and revisit complex concepts.

• Exercise:

• Develop an intermediate dashboard incorporating calculated fields, parameters, and geographic maps.

• Share your dashboard on Tableau Public or present it as a portfolio piece.


Week 3: Advanced Tableau Techniques


Day 15: Table Calculations


• Topics:

• Understanding table calculations like running totals, moving averages, and percent of total.

• Advanced table calculations (rank, percent difference).

• Resources:

• Tableau Help: Table Calculations

• YouTube Video: Table Calculations in Tableau

• Exercise:

• Implement running totals and moving averages in your sales dashboard.

• Use table calculations to rank products by sales performance.


Day 16: Advanced Visualizations


• Topics:

• Creating heat maps, highlight tables, and bullet graphs.

• Using dual-axis and combination charts for advanced insights.

• Resources:

• Tableau Blog: Advanced Visualizations

• YouTube Video: Advanced Charts in Tableau

• Exercise:

• Develop a heat map to display sales density across regions.

• Create a bullet graph to compare actual sales against targets.


Day 17: Dashboards and Stories


• Topics:

• Building interactive dashboards.

• Creating data stories to convey insights effectively.

• Resources:

• Tableau Tutorial: Dashboards

• YouTube Video: Creating Dashboards in Tableau

• Exercise:

• Combine multiple visualizations into a cohesive dashboard.

• Use actions (filter, highlight, URL) to add interactivity.

• Create a story by sequencing dashboards to narrate a data-driven narrative.


Day 18: Data Blending and Relationships


• Topics:

• Deep dive into data blending techniques.

• Understanding Tableau’s data relationships (logical vs. physical).

• Resources:

• Tableau Help: Data Relationships

• YouTube Video: Data Relationships in Tableau

• Exercise:

• Blend multiple data sources to enrich your analysis.

• Create visualizations that leverage data from different sources seamlessly.


Day 19: Advanced Calculations and LOD Expressions


• Topics:

• Mastering Level of Detail (LOD) expressions for complex calculations.

• Using FIXED, INCLUDE, and EXCLUDE in LOD expressions.

• Resources:

• Tableau Tutorial: LOD Expressions

• YouTube Video: LOD Expressions in Tableau

• Exercise:

• Create LOD expressions to calculate average sales per customer across regions.

• Use FIXED LOD to compare individual performance against overall metrics.


Day 20: Parameters and Dynamic Calculations


• Topics:

• Advanced use of parameters in dynamic calculations.

• Creating user-driven scenarios and simulations.

• Resources:

• Tableau Tutorial: Advanced Parameters

• YouTube Video: Dynamic Calculations with Parameters

• Exercise:

• Develop a parameter-controlled dashboard where users can adjust targets and see real-time impact on performance metrics.


Day 21: Review and Advanced Project


• Review:

• Recap all advanced topics covered during the week.

• Ensure understanding of complex concepts like LOD expressions and advanced calculations.

• Exercise:

• Build an advanced dashboard that incorporates table calculations, LOD expressions, and dynamic parameters.

• Present your dashboard as a case study in your portfolio.


Week 4: Special Topics and Capstone Project


Day 22: Tableau Prep and Data Cleaning


• Topics:

• Introduction to Tableau Prep for data cleaning and transformation.

• Building and optimizing data flows.

• Resources:

• Tableau Prep Getting Started

• YouTube Video: Tableau Prep Basics

• Exercise:

• Use Tableau Prep to clean and prepare a messy dataset for analysis.

• Perform tasks like removing duplicates, splitting columns, and creating calculated fields.


Day 23: Advanced Mapping Techniques


• Topics:

• Custom geocoding and spatial files.

• Enhancing maps with layers and advanced settings.

• Resources:

• Tableau Tutorial: Advanced Mapping

• YouTube Video: Custom Maps in Tableau

• Exercise:

• Create a custom map using latitude and longitude data.

• Add multiple layers to your map to show different data dimensions.


Day 24: Integration with R and Python


• Topics:

• Connecting Tableau with R and Python for advanced analytics.

• Using calculated fields with R and Python scripts.

• Resources:

• Tableau Help: R Integration

• YouTube Video: Tableau and R Integration

• Exercise:

• Set up R or Python integration with Tableau.

• Create a visualization that uses an R or Python script for advanced statistical analysis.


Day 25: Performance Optimization


• Topics:

• Best practices for optimizing Tableau workbook performance.

• Reducing load times and improving interactivity.

• Resources:

• Tableau Performance Guide

• YouTube Video: Optimizing Tableau Performance

• Exercise:

• Analyze and optimize an existing dashboard for better performance.

• Implement techniques like data extracts, indexing, and efficient calculations.


Day 26: Storytelling with Tableau


• Topics:

• Crafting compelling data stories.

• Using Tableau’s Story feature to present data narratives.

• Resources:

• Tableau Tutorial: Story Points

• YouTube Video: Storytelling in Tableau

• Exercise:

• Create a Tableau Story that guides viewers through a data-driven narrative.

• Use multiple dashboards and visualizations to support your story.


Day 27: Tableau Server and Online Sharing


• Topics:

• Publishing dashboards to Tableau Server or Tableau Online.

• Managing permissions and user access.

• Resources:

• Tableau Help: Publish to Tableau Server

• YouTube Video: Publishing to Tableau Server

• Exercise:

• Publish your dashboards to Tableau Public or Tableau Online.

• Share your visualizations with others and gather feedback.


Day 28: Introduction to Tableau Extensions and APIs


• Topics:

• Enhancing Tableau with extensions and APIs.

• Using Tableau’s JavaScript API for custom integrations.

• Resources:

• Tableau Extensions

• YouTube Video: Tableau JavaScript API

• Exercise:

• Explore and integrate a Tableau extension into your dashboard.

• Experiment with basic API calls to customize dashboard functionality.


Day 29: Capstone Project Planning


• Topics:

• Selecting a real-world dataset.

• Planning your capstone project workflow.

• Resources:

• Kaggle Datasets

• Tableau Public Gallery for Inspiration

• Exercise:

• Choose a dataset that interests you (e.g., sales, healthcare, finance).

• Outline the objectives and key metrics for your capstone project.


Day 30: Capstone Project Execution and Presentation


• Exercise:

• Develop a comprehensive Tableau dashboard based on your chosen dataset.

• Incorporate various techniques learned over the past 29 days (calculated fields, parameters, advanced visualizations, interactivity).

• Document your process and insights in a report or Tableau Story.

• Present your project to peers, mentors, or online communities for feedback.


Additional Resources:


• Books:

• “Learning Tableau” by Joshua N. Milligan

• “Tableau Your Data!” by Daniel G. Murray

• Online Courses:

• Coursera: Data Visualization with Tableau Specialization

• Udemy: Tableau 2023 A-Z: Hands-On Tableau Training for Data Science

• Communities and Forums:

• Tableau Community Forums

• Tableau Subreddit

• Practice Platforms:

• Makeover Monday

• Tableau Public Gallery


Tips for Success:


1. Consistency: Dedicate a specific time each day for learning and practicing Tableau.

2. Hands-On Practice: Apply what you learn immediately through exercises and projects.

3. Join Communities: Engage with Tableau communities to seek help, share your work, and gain inspiration.

4. Seek Feedback: Regularly share your dashboards with others to receive constructive feedback.

5. Stay Updated: Tableau regularly updates its features. Keep an eye on the latest releases and incorporate new functionalities into your learning.


By following this structured 30-day plan, you’ll develop a strong proficiency in Tableau, enabling you to create insightful and impactful data visualizations and dashboards. Happy learning!

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(Refresh the page if you want to view the gif image multiple times. Or go to Tableau Public and click the button at the top-right corner.)

Jake and I collaborated on a dashboard. He told me that he learnt a way to create an in-place help page in Tableau.

(Addendum: Jonathan Drummey has a much better Tableau-only solution that I missed from his presentation. I only caught later part of the presentation.

[Forward: I asked ChatGPT o1-mini who then wrote this. Hope it helps. All the credit and the blame go to ChatGPT.

I went over the plan and it looked decent. Whether it can be done in 30 days or not, it depends on the person and the time he spends on it.

Mundane charts are those basic ones that all data visualization beginners can create, possibly with Show Me in Tableau. They are the boring ones at times because many people tend to create fancier ones just to show off.

A while ago, Sharon came to me asking a question regarding Pareto Chart Multiples. That is, per each category, there is a Pareto chart. And we need to create Pareto charts for all the categories.

[Update: The product manager Wilson Po alerted me that the Viz Extension is still a work in progress. It will not be part of the incoming version 2024.1. Instead, it will be released later in 2024. Just be patient]

Tableau 2024.1 is coming. I got a chance to test drive it.

Buzzfeed recently asked Midjourney to draw images of people in 50 US states.  So the AI drawing tool created 50 images of couples that represent its perception of the people in each state.

I just put the images into a tiled map in Tableau. Each image is added as a background in each tile.

1

The folks at Business Expert had a brilliant idea. They asked AI's perception on UK banks as a dog. I am inspired to do the same on US banks.

ChatGPT is asked to confess its perceptions on top US banks as a dog. Then Midjourney is tasked to generate the images.

Through my previous post on the new Sankey chart type, I got in touch with Wilson, the product manager leading the development of this new chart type. I made some comments on creating multi-level Sankey via cascading of single Sankey's.

As an enthusiastic user of Sankey charts, I am excited to learn that a Sankey chart type is being piloted in Tableau Public (Web Edit only). I wrote about Sankey chart design in multiple posts. Sankey chart may appear in different forms depending on applications.

Just came across a report by Reuters on USA-China gap widens between respective internet giants. The report includes a text table. The caption says the table columns can be sorted. But it is a static image. (They retracted the table after I reported the issue.)

It picked my interest.

1

In the process of creating a dashboard on the US Travel Advisory 2023, I found some mismatches in a few regions in two countries.

Gaza Strip

One is Gaza Strip in Palestinian Territories. In the latter, there are two regions: Gaza Strip and West Bank.

This is a follow up post to Fiscal Calendar Calculations Cheatsheet for Tableau.

Excel is a very important tool for data analysis and calculations. It's also an important data repository for Tableau.

Week-based calendars are used in many companies as their fiscal calendars. The total weeks in a fiscal year is 52 weeks, that is, 364 days. Each quarter has 13 weeks. There are 3 varieties of 13 weeks: 5-4-4, 4-5-4 and 4-4-5 weeks per quarter. In leap years, there are 53 weeks or 371 days.

Christine suggested me to have a look at Simpson's Paradox, following my recent posts on Anscrombe's Quartet and Datasaurus Dozen. They are all about learning to look at statistics in an impartial way.

#TweakThursday: From time to time I tweak someone else's public viz and try to make it better to my subjective view.

This post is about 13 data sets, known as Datasaurus Dozen, that have the same stats and different distributions. Stats can be deceiving while data visualization can makes a big difference.

Francis Anscombe, a British statistician and a professor at Princeton and Yale, constructed 4 different sets of data which all have the same stats, known as Anscombe's quartet. However the quartet's data distributions are quite different. 

Stats alone can be deceiving.

In a single day, I am asked twice the same question: how to install database drivers for Tableau in Mac? The question of the day is regarding the drivers for Presto and PostgreSQL databases. The docs online may not answer the question exactly.

There are always more than one ways to skin a cat. In Tableau, there is always one more way to design the same chart. Mastering them will give us more options to satisfy the various requirements we may be asked for.

Line chart is one of the most basic ones.

I almost named the post as Charting "Top N and Others" via Post-filtering. Read on to understand why.

Visualizing "Top N and Others" is an often required business use case. A popular solution is by creating a top N set. That's the one I have been using through the years.

Angel works in Finance. She often asks me questions on calculations in a table. Today I got this question: How to calculate Year over Year (YoY) change ratios for both quarterly and yearly sums, in a single sheet?

Here is the solution we got. First there are two parts for the YoY calculation.

Just came back from Tableau Conference 2022 at Las Vegas. What an exciting event! The most exciting thing is reuniting with old friends and meeting with the datafam people known online for years.

Attended first time the Tableau Visionary summit.

A little enhancement in the formula editor can make a big difference for whose who create formula all the time in Tableau. Here are my wishes for a future editor. 

Highlighting Syntax Words

Currently a formula in Tableau can look plain and a bit uninspiring.

For the sake of uniformity in a bar chart, we may need to filter out dates in the latest partial week, month, quarter or year. That is what Parinita asked me about a filter to do just that.

Before Belinda asked me about making phone calls from Tableau dashboard, she had some issues in creating an email template in Tableau. Many people might have known how to do the basics.

Belinda needs to call business partners in foreign countries regularly. She has a dashboard showing various deadlines that she has to monitor. If a deadline is overdue, she may need to talk to the partner in question. She has already integrated email in the dashboard via URL action.

This post is about labeling a trellis chart that's already in dual axis.

In earlier posts on labeling trellis chart, we use one axis for the labeling function. Many times, the chart is already in dual axis (both axis are taken).

In online Tableau literature, I noticed that most people referred to Zen Master Chris Love's formula in a 2014 post about the size of a trellis chart.

Sharon left a message in my last post on Labeling Trellis Chart Anywhere asking whether we can have one label on the left and another on the right per trellis chart cell in Tableau. Yes we can. Below we will show how to place multiple labels within a trellis cell.

Catherine came to my office asking if we can create a compact version from a sparse table in Tableau, so that the table would look a lot more compact. This allows a succinct view of the table content. It saves screen real estate and makes it easy to read for business audience.

In my previous post on labeling trellis chart, I only showed how to label at the top left corner. People like Chipo Chirewa may want to label elsewhere.

Here I would show how to label anywhere in a trellis cell, like places other than the top left corner.

3

[Sequel to this post: Labeling Trellis Chart Anywhere]

To many people, the most difficult part of creating a trellis chart is to label it. Especially labeling it in the same sheet and with sparse data is even harder.

1

Many times, Tableau is used beyond data visualization. Often we need to perform all sorts of functions. Actually, Tableau is a powerful calculator. Instead of using another tool, such as Python or Excel, we can do it in Tableau proper.

Here is a use case at work where the grand total of a table needs to be accumulated horizontally to the right.

In the table, daily sales are shown by categories. The expected result is as follows:

We will use customized grand total technique to calculate it.

The term Fill Down is from Excel where we may need to fill all the empty cells below a non-null cell with the same cell value. Excel has a Fill Down button in the menu bar for a single cell fill down. We may also have to fill down between multiple non-null cells in the same column.

In data analysis, we need to use filters here and there. In general, we would classify them as pre-filters or post-filters for better understanding of their respective mechanisms.

A pre-filter works on the data set. It only keeps the data we need for the analysis.A post-filter works on the results.

2

Note first that here I loosely define data densification as what includes both interpolation and extrapolation of data marks as well as their associated values.

[ This is a guest post by Hans Romeijn. This is a followup post to my recent post on calculating YTD/YoY, QTD/QoQ, MTD/MoM and WTD/WoW. Hans shows a practitioner's approach to the calculation with performance in mind.

I was asked a question: How to find out the IDs that showed up consecutively 5 times during the last 14 days?

How would you solve it?

Here I came up with 2 solutions. The 2nd one is a little simpler.

1

In corporate finance, bridge chart is often used to visualize itemized sales/revenue performance during a particular period, such as a quarter or a year.

Bridge chart can be designed using waterfall chart. But we will use a different approach.

A colleague posted this: "Hi Team, may I ask if you have any good idea to show the % difference of two randomly selected data points on a line chart?"

I found a solution to it, which is as follows.

The show/hide buttons in containers and also in sheets allow us to create drill down functionalities in Tableau dashboards. Actually they make it simple to drill down in more ways than before.

Drill down with fixed sized containers

Here is an example. Given a simple bar chart by category.

Subtitle: Sunburst Chart with Labels Inside and Categorical Sequential Colors

Here I am presenting how to design Sunburst Chart with practical considerations, such as:

Labels insideCategorical sequential colors with dynamic data.The design will be based on map layers, a new feature since Tableau d

[ Followup guest post by Hans Romeijn: Calculating Period-To-Date/PoP with Indicators for Better Performance ]

Year to Date (YTD) and Year over Year (YoY) calculations are very important in business dashboards. Jim Dehner recently wrote a great post on the topic.

9
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