Extracting insight from data takes more than charts—it takes analytical thinking. This course develops participants’ ability to apply Tableau for data cleaning, transformation, and statistical analysis. They will practise through practical exercises and real-world case scenarios.
Learning Outcomes:
Analyse datasets and uncover trends using Tableau
Combine data sources and manage data relationships
Build interactive visualisations for decision support
Use advanced chart types and analytics functions
Key Topics:
Tableau data blending and joins
Time-series and trend analysis
Calculated fields and analytics tools
Advanced visualisation types (e.g., Gantt, box plots)
Sharing and publishing dashboards
Module 1: Data Collection, Ingestion and Preparation
Prior to visualization and analytics, it is imperative to make that the data you use is clean and ready for visual analysis. This module takes you through the concepts of various data sources, how data is collected and how you prepare and make the data ready.
● Introduction to Data Sources
● Data Collection Mechanisms – How should you collect data?
● Data Cleaning methods
o Dealing with missing values
o Dealing with improper values and strings
o Duplicate rows
o Dealing with dates
o Extracting data
o Creating new data
● Creating a data model
Module 2: Data Normalization and Tables
One of the important parts of data analytics is making sure data is in the most optimized form. Non optimized data tends to slow down visualizations and makes the process messy. This module will recap a few concepts of data normalization and the basic normal forms of data along with the main types of tables that should exist in a dataset.
● What is Data Normalization?
● Normalizing a dataset
● Understanding Fact and Dimension Tables
Module 3: Understanding Data Storytelling
The aim of using data is to present actionable insights using the right dashboards, charts, metrics, and story. It is important to convey the right message to the right people. In this module participants will learn about
● Key elements of data storytelling
● Formulating business questions relevant to the data
● Introduction to KPIs and key KPIs
● Visualizations and their implications
● What differentiates good and bad visualizations?
Module 4: Tableau Overview
Tableau is a software which has many rich features. In this module participants will get a high-level understanding of the capabilities of Tableau and will start working with the Tableau interface
● What is Tableau?
● Tableau Software
● Tableau File Types
● Explore Tableau Interface
Module 5: Data Sources, Worksheet and View
As part of analytics and visualization, getting your data ready is the first step. This module covers the basics of working with the data to prepare it for further visualization and analytics. Participants will learn the following as part of this module.
● Connecting to different data sources
● Create relationships between tables
● Create data extracts and filters at data source
● Understanding Dimensions and Measures
● Basics of worksheets and views
● Create Folders and Hierarchy
Module 6: Charts, Graphs and Formatting
The next step towards analytics and visualizations is to summarize the data and create the right charts and graphs to present data in the most precise manner. In this module participants will learn:
● Create different charts for different scenarios
● Formatting size, colors, and other elements of charts
● Gathering insights from charts
Module 7: Organize and Transform Data
In many cases, you would require organizing, transforming, or creating new data fields to make data visualization more effective. This refinement helps analysts to find better insights from the data. In this module, participants will learn:
● Create Filter from measures and dimensions
● Apply Filters to Charts
● Organize Data by groups and sets
● Create calculated fields and parameters
● Apply logical functions
● Top N Analysis
Module 8: Advanced Analytics
Many a time, you would want to employ analytics to get quick insights from your data. Tableau presents such advanced analytics features which can be directly applied to various charts and graphs. In this module participants will learn about:
● Create trend and average lines to make charts more insightful
● Forecast future values using built in methodologies
● Create clusters in the data and visualize them
● Create and fit regression lines
Module 9: Maps (Internal and External)
Map services are used to show geographical insights in a visually appealing manner. This module covers the basics of how maps can be used and the different kinds of maps that can be added to Tableau to provide more detailing.
● Map Basics
● Adding markers to maps
Module 10: Creating Analytical Dashboards
Creating insightful dashboards are critical to all sectors. Dashboards and reports are designed to help managers, executive draw insights and conclusions by viewing interpretable data, understand the cause and effect and implement further plans accordingly. In this module participants will learn how to create an insightful dashboard.
● Creating dashboards from charts and graphs
● Formatting dashboards to make them interpretable
● Creating filters for dashboard visualizations
● Adding images and annotations to dashboards
● Publishing a dashboard to Tableau public
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