December 3, 2023

How to Learn Tableau in 2024 : A Comprehensive Guide

Ready to make your data shine? Our Tableau Comprehensive Guide is here for you! Whether you're just starting or want to get better, we've got simple steps to help you become a Tableau expert. Let's get started and make data visualization simple and enjoyable!

There is an ongoing demand for people who are able to interpret  data through simple visualizations in an increasingly data-centric world. One of the ways of doing this is through Tableau, a powerful tool that empowers individuals to transform complex datasets into insightful visual narratives.  So , if you wish to  learn Tableau and be a part of the data revolution, this is the perfect guide for you. This blog will walk you through the steps to learn Tableau in the easiest way possible. 

What is Tableau?

Tableau is a versatile data visualization tool used by data analysts and scientists. It connects to various data sources, enables interactive visualizations, and facilitates easy sharing. Its user-friendly interface supports drag-and-drop features, making it accessible for beginners. Widely adopted across industries, it aids businesses in making data-driven decisions.

Why  should you learn Tableau ?

Learning Tableau can enhance your data analysis and visualization skills, opening up opportunities in various industries where data-driven decision-making is crucial. The salaries for Tableau professionals are the best in the IT industry. Thus making it one of the major reasons why you should be learning it.

Key features of Tableau

  • Enables quick visualization with minimum development time.
  • Easy to use for creating interactive dashboards.
  • Provides direct connection with databases and data warehouses.
  • Can handle enormous amounts of data. 
  • Its cross-platform accessibility enhances user reach and flexibility.

Job Prospects for Tableau Developers

Tableau developers have varied roles; many positions don't require a computer science or data science degree, welcoming diverse backgrounds. According to Zippia reports—there are a whopping 84,000+ job opportunities for Tableau developers in the United States alone🚀🌏. In India, the job scene is buzzing too, with over 3,000 Tableau jobs waiting for both beginners and experienced professionals.

As per Gartner’s magic quadrant 2023, Tableau ranked 1st in the leader for BI products for the 11th consecutive time. Common roles related to Tableau development include: Tableau Developer, Business Intelligence Analyst, Data Visualization Specialist, and Reporting Analyst. According to Glassdoor the average salary for a tableau developer in India is ₹7LPA. Popular companies hiring for this role include TCS, Accenture, Infosys and Tech Mahindra.

How to learn Tableau?

Step 1: Familiarity with User Interface & Data Connections. 

1. Get to know the user interface 

The path to becoming a Tableau specialist begins with being acquainted with its user interface. The trial version of Tableau Desktop is available for download from the Tableau website and is valid for 14 days.  Install it on your machine by following the instructions on the website.

After completing the installation process to get started with the product you can refer to the free online courses provided on the Tableau website.

Here are some resources to assist you with this step:

Youtube Channels to follow: 

2. Making data connections 

Before getting started with the visualizations you need to  connect to your data source. Tableau seamlessly connects to diverse sources—Excel, databases, text, CSV, and data servers like Tableau Server, Google Analytics, Google Big Query, and more, ensuring high-speed access.

You can explore some sample datasets to get started  here: Free Public Data Sets For Analysis | Tableau

Step 2: Learn the basic skills

To build a foundational knowledge  learn :

1. Playing  around with basic charts such as: 

  • Bar chart: Visually represents data with rectangular bars. It's effective for comparing categories and their quantities.
  • Line chart: Connects data points with lines, showing trends over time. Useful for illustrating continuous data patterns or fluctuations.
  • Scatter plot: Displays points on a two-dimensional graph, each representing a combination of two variables. It reveals relationships and trends.
  • Pie chart: Represents parts of a whole. Each slice represents a proportion, making it easy to understand the contribution of each category.

2. Data sorting: Find out how to sort data by ascending or descending order and apply them to your analysis based on the context.

3. Data grouping: Use the grouping function to aggregate data at different levels, making it easier to analyze trends and patterns.

4. Filtering techniques:

  • Measure filters : Restrict data based on numerical values
  • Dimension filters : Refines data based on categorical variables
  • Data source filters: Controls the data that enters Tableau from the source

3. How to work with different data sources like data connection , joins & unions and data blending. Look at the following resources to get familiar with these basics:

4. Data Cleaning: Learn data cleaning features like handling missing values, removing duplicates, and filtering outliers. 

Step 3: Intermediate Tableau Skills

1. Intermediate analysis techniques 

Explore intermediate level charts and graphs 📈 such as:

1. Heat maps : Visualize data in a matrix using colors to represent values. Useful for displaying patterns and variations in large datasets.

2. Box plots: Show the distribution of data, including median, quartiles, and outliers. Helpful for understanding the spread and skewness of values.

3. Bump Chart: Display the ranking and changes in rank over time. Ideal for visualizing trends and movements in data, such as sports team rankings.

4. Donut Chart: Similar to a pie chart, but with a hole in the center. It represents the parts of a whole, providing a clearer view of the data.

5. Waterfall Chart: Shows incremental changes in values, often used for financial data. Shows how each value contributes to the overall total.

6. Motion charts: Display changes in data over time, using animations to show transitions. Useful for visualizing trends and patterns in dynamic datasets.

7. Mapping: Tableau's mapping capabilities enable geospatial visualization. Learn to  connect to geospatial data, create basic and custom maps, use symbol, filled, and path maps, apply filters, annotations, and interactive features. Leverage geographic calculations for insightful analysis, providing dynamic and engaging geospatial visualizations.

Implementation of formulas  and calculations and using functions  (aggregation, logic, date, etc.)

2. Storytelling with dashboard creation using interactive features

Dashboards offer a comprehensive data overview, empowering you and others to gain insights efficiently. Consider purpose, audience, and consumption method when creating. After defining objectives, enjoy designing your dashboard! Learn about: 

  • Adding views and objects to dashboards,
  • Applying Filters to dashboard,
  • and various Layouts and formatting options culminating in the creation of interactive dashboards and storyboards.

Step 4:  Learn  Advanced Analysis  with Tableau

After you feel confident in your ability to create visualizations, you may use Tableau to conduct more advanced  analyses. 

1. Segmentation and cohort analytics: Segmentation in Tableau divides data for pattern analysis. Cohort analytics studies group behavior over time. Both aid strategic decisions, offering targeted insights in areas like marketing and customer retention through informed data analysis.

2. Table calculations and level of detail (LOD) expressions: Table calculations in Tableau enable dynamic computations within visualizations, responding to changes in data. Level of Detail (LOD) expressions allow precise control over aggregation, providing detailed or summary insights.

3. Time series and predictive analysis: Tableau simplifies time series analysis, revealing seasonal trends and variable changes over time. The user-friendly interface aids in understanding data patterns, facilitating informed decision-making and predictive insights.

4. Learn advanced chart types like :

  • Sunburst Chart
  • Population Pyramid
  • 3D Scatter Plot
  • Pareto Chart
  • Hexbin Map

Learn more about advanced analytics here:

Step 5: Project portfolio and community building 

1. Create a Tableau project portfolio

Showcase your projects and visualizations on platforms like Tableau Public , Linkedin or  GitHub. Sample datasets to help you get started:

  • Covid 19  activity: A global time series of covid cases and death data.
  • Airline prices: Data of various airlines regarding their source and destination cities, prices and duration. 

Websites to get datasets for your portfolio: 

  • Official data published by the US government.
  • Statista: Market research datasets
  • Kaggle: Datasets belonging to all domains such as sports, finance  etc. 

2. Join community & groups

Engage with forums and communities for ongoing learning.This will help you a lot to enhance your learning, get answers to questions and simplified description for complex topics by experts. You can join Tableau Community  and Tableau Public to share your projects and join discussions. 


Step 6 :Getting Certified

1. Tableau Desktop Specialist Certification:

  • Consider taking the Tableau Desktop Specialist exam for formal recognition.

2. Tableau Certified Consultant:

  • If you feel confident, you can pursue the Tableau Certified Consultant certification.


Starting your Tableau journey as a beginner might feel like a lot, but keep in mind that everyone starts somewhere. Follow this guide, practice regularly, and enjoy the learning process. As you go along, you'll not only get good at Tableau but also find the satisfaction of turning data into useful insights.

Happy analyzing! 🌐💻

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