In this section, we will explore the fundamental data types and structures that Tableau uses to manage and visualize data. Understanding these basics is crucial for effectively working with data in Tableau.

1. Data Types in Tableau

   • String (Text)
   • Number (Whole and Decimal)
   • Date and DateTime
   • Boolean
   • Geographic

2. Data Structures in Tableau

   • Tables
   • Fields
   • Rows and Columns

3. Data Roles

   • Dimensions
   • Measures

• Description: Represents text data.
• Example: Names, categories, descriptions.
• Usage: Used for labels, categories, and any non-numeric data.

• Description: Represents numeric data.
• Example: Sales figures, quantities, percentages.
• Usage: Used for calculations, aggregations, and quantitative analysis.

• Description: Represents dates and times.
• Example: Order dates, timestamps.
• Usage: Used for time series analysis, trend analysis, and date-based calculations.

• Description: Represents true/false values.
• Example: Flags, binary states.
• Usage: Used for conditional logic, filters, and binary categorization.

• Description: Represents geographic data.
• Example: Country, state, city, latitude, longitude.
• Usage: Used for mapping and spatial analysis.

• Description: The primary structure for storing data in Tableau.
• Example: A table containing sales data with columns for product, date, and sales amount.
• Usage: Used to organize and manage data in a structured format.

• Description: Columns in a table, representing different attributes of the data.
• Example: Product Name, Sales Amount, Order Date.
• Usage: Used to define the data attributes and are the building blocks for visualizations.

• Description: Rows represent individual records, and columns represent the attributes of those records.
• Example: Each row in a sales table represents a single sale, with columns for product, date, and amount.
• Usage: Used to organize data in a tabular format for easy access and analysis.

• Description: Qualitative data used to categorize, segment, and reveal the details in your data.
• Example: Product categories, regions, customer names.
• Usage: Used to slice and dice the data, providing context and structure to the analysis.

• Description: Quantitative data that can be measured and aggregated.
• Example: Sales amount, profit, quantity sold.
• Usage: Used for calculations, aggregations, and quantitative analysis.

Let's consider a simple dataset of sales transactions:

• Order ID: Number (Whole)
• Product Name: String (Text)
• Sales Amount: Number (Decimal)
• Order Date: Date
• Region: String (Text)

Task: Identify the data types and roles for the following dataset:

Solution:

• Customer ID: Number (Whole), Dimension
• Customer Name: String (Text), Dimension
• Purchase Amount: Number (Decimal), Measure
• Purchase Date: Date, Dimension
• Membership: Boolean, Dimension

Understanding the basic data types and structures in Tableau is essential for effective data analysis and visualization. By recognizing the different data types and their roles, you can better organize and manipulate your data to create meaningful insights. In the next module, we will dive into basic visualization techniques to start bringing your data to life.