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
• Creating a data model
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
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
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
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
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, colours and other elements of charts
• Gathering insights from charts
Organize & Transform Data, Calculations and Functions
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
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
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
• External Map Services (Mapbox) to create more detailed maps
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
Statistics Behind Good Storytelling
• Sample size and inference – Why is it important?
• Correlation and causation – Applied examples
Common Data Storytelling Pitfalls
Data Storytelling needs to be done the right way. There can be cases when the story doesn’t go right, and you should be aware of those! This module deals with the basic pitfalls during storytelling.
• The Giant Outlier Problem
• The Pasta Line Chart Problem
• The Occlusion Problem
Participants will have an opportunity to create a visually stunning and insightful dashboard and publish it to their Tableau public profile. The case study ensures that participants can apply what they have learnt from the training, right from data ingestion to create and build interactive and informative dashboards.