Data Analysis and Visualization with Tableau

Tableau software allows businesses to clearly visualize, analyze, and report large data sets. In the industry, Tableau is a business intelligence tool used to make decisions supported by data. In order to develop effective dashboards and data visuals that can be studied and interpreted, learners must understand the UI and basic features. 

This week will cover

• Basics and Installation of Tableau
• Types of Products and Roles
• Interface and Workflow
• Tableau Dashboards vs PPT
• Connecting to Data
• Data Source & its Types
• Live and Extracts Connections

The Tableau workspace has features such as shelves, cards, the Data Pane, Analytics  Pane, toolbars, and menus. Each of these features has a specific function that learners must understand how to use when working with Tableau.

This week will cover 

• Basics of Data Pane
• Quick Visualisations
• Marks and its Properties
• Pages Shelf
• Menu and Toolbar
• Analytics Pane

As not all types of data are the same, Tableau supports 7 different data types, which can be sorted and grouped according to requirements. In order to present and organize data visually, learners should understand the features of Tableau related to data types and sorting. 

This week will cover 

• Sheet Interface
• Data Types
• Dimensions and Measures
• Sorting & Custom Sort and Grouping
• Sets & Combines Sets and Hierarchies
• Highlight Data
• Split & Custom Split

There are six different filters available for users on Tableau, each with their own unique function. By using filters, datasets can be condensed to illustrate concise information, thus improving the efficiency of dashboards. Data in a table can also be analyzed through performing table calculations. These features are essential for learners, as they can be used to develop efficient and concise dashboards. 

This week will cover 

• Filters, Filter Types, and Order Process
• Highlighted Data
• Context Filter and its Uses
• Calculated Fields
• Aggregations and their Uses
• Table Calculations
• Level of Detail Expression (LODs)
• Bins and its Uses

Spreadsheets with data can be transformed into visually interactive dashboards that present the information. Dashboards can be combined with spreadsheets to tell a story and narrate performance through measured parameters. By learning the best practices, learners can design and develop effective dashboards and stories for businesses. 

This week will cover 

• Parameters
• Action Filters
• Dashboard Layout
• Sizing and Object
• Formatting
• Stories
• Best Practices

Tableau workbooks can be shared, exported, and published as required. As many individuals may work on a dashboard together, it is important for learners to understand how distribution and publishing work. 

This week will cover 

• Distribution
• Exporting
• Workbook File Types
• Publishing
• Replacing Data Sources

Tableau is also used to perform data blending and data joining. Through joining, data in tables and sheets from the same source can be combined. Data blending lets users combine data from different sources. It is important for learners to understand joins and blending as both are often required in the industry.

This week will cover 

• Joins
• Inner and Outer Join
• Left and Right Join
• Blending
• Union

When analyzing data on Tableau, Relationships let you combine data from different tables. It is important for learners to understand how to work with multiple sets of data for effective analysis and visualization. 

This week will cover 

• Relationships
• Data Models
• Relationships vs Joins
• Creating and Optimizing a Relationship
• Types of Relationships
• Smart Aggregations and their Types

Before data is used in business intelligence, it goes through data preparation. This involves collecting, combining, and systematically organizing the dataset before it gets processed. It is important for learners to understand the parameters considered when preparing data. 

This week will cover

• Pivot
• Custom Split
• Hide & Unhide Fields
• Sampling the Data
• Interactivity
• Parameter Actions
• Set Actions

When working with large sets of data, Tableau lets users perform advanced calculations and analytics to draw accurate inferences. It is important for learners to understand how to perform advanced calculations using Tableau to meet industry standards. 

This week will cover 

• Advanced Calculations
• Regular Expressions
• Table Calculations
• Use Cases
• Trend Lines
• Clustering and Forecasting

Nested LOD is an advanced topic in Tableau that lets users assess data sets in-depth. Users can also build maps using Tableau, and understand the related data. As certain data sets may require mapping functions, and analysis in-depth, it is important to know about these concepts. 

This week will cover

• Nested LOD and Use Cases
• Geo Mapping
• Geospatial Data and Use Cases
• Standard Maps
• Map Hierarchies
• Map Layers
• Background Maps
• Common Issues

Through dynamic designs, values in dashboards can automatically change when related data is modified. As it is common for data sets to have changing values, knowing how to work with dynamic designs is an essential skill for learners. 

This week will cover

• Dynamic Designs
• Ways to Create
• Interactivity
• Extensions
• Tooltip in Visualizations
• Performance Recording
• Design Principles