Tableau Session 01: Introduction to Tableau

WORKBOOKS
DATA TYPES
FIELDS
BASIC CHARTS
FILTERING

Learning Goals

  • Understand the role of Tableau in data analysis and business intelligence
  • Connect Tableau to Excel datasets
  • Understand Tableau products and file types
  • Navigate the Tableau interface
  • Understand Tableau data concepts including data types, dimensions, measures, discrete and continuous fields
  • Create basic visualizations using the Airbnb dataset
  • Add interactivity using filters, groups, sets, and sorting
  • Build and publish a simple Tableau dashboard

Overview

This session introduces the foundations of Tableau, a leading platform for interactive data visualization and business intelligence.

You will learn how Tableau connects to data, how the interface is organized, and how data fields are transformed into visualizations.

Throughout this session we will use the dataset:

Dataset: airbnb.xlsx

The dataset contains Airbnb listings with fields such as:

  • Listing name
  • Neighborhood
  • Property type
  • Room type
  • Number of beds
  • Price
  • Number of reviews
  • Host start date

Why Data Visualization Matters

Data visualization helps transform raw data into insights that humans can quickly understand.

Instead of analyzing tables of numbers, visualizations allow analysts to:

  • Identify trends
  • Compare categories
  • Detect anomalies
  • Communicate insights clearly

Visualization is therefore a critical step in data-driven decision making.

Tableau in Data Analysis

Tableau is a data visualization platform used to explore data and build interactive dashboards.

Instead of writing complex queries, analysts interact with data using drag-and-drop fields.

Typical Tableau workflow:

flowchart LR
A[Raw Dataset] --> B[Connect Data]
B --> C[Explore Fields]
C --> D[Build Visualizations]
D --> E[Create Dashboard]
E --> F[Share Insights]

Downloading Tableau Desktop

Tableau Desktop can now be downloaded for free for learning and development purposes.

The desktop application provides the full authoring environment used to build visualizations, dashboards, and data analysis workflows.

Download Link

Download Tableau Desktop

Installation Steps

  1. Download the installer from the official Tableau website
  2. Install Tableau Desktop on your computer
  3. Launch the application
  4. Sign in with a Tableau account if prompted

Publishing Dashboards

Once visualizations and dashboards are created in Tableau Desktop, they can be published online using Tableau Public.

Tableau Pablic Link

Tableau Pablic

Tableau Public is a free platform that allows users to share interactive dashboards on the web.

To publish a dashboard:

  1. Create a Tableau Public account
  2. In Tableau Desktop select:
File → Save to Tableau Public
  1. Sign in to your Tableau Public account
  2. The workbook will be uploaded and made publicly accessible

After publishing, dashboards can be:

  • Shared through a public URL
  • Embedded in websites
  • Viewed and interacted with directly in a browser

Tableau Public is commonly used for:

  • Portfolio projects
  • Data storytelling
  • Public data analysis
  • Sharing visualizations with the community

Tableau Products

Tableau includes several products that support different stages of analytics.

Product Description
Tableau Desktop Tool for creating dashboards and visualizations
Tableau Server Platform for sharing dashboards within organizations
Tableau Cloud Cloud-hosted version of Tableau Server
Tableau Public Free platform for publishing dashboards publicly
Tableau Prep Tool for data cleaning and preparation
Tip

Tableau Desktop is now free, making it easier for analysts and students to learn Tableau.

Tableau File Types

File Type Extension Description
Workbook .twb Stores visualizations and connections without data
Packaged Workbook .twbx Workbook containing embedded data
Data Source .tds Connection metadata
Packaged Data Source .tdsx Data source with extract
Extract .hyper Optimized local data storage

Tableau Menu Bar

The Menu Bar is located at the top of the Tableau interface and provides access to the main commands used for managing data, creating visualizations, formatting dashboards, and controlling the application environment.

Tableau Menu Bar

Each menu contains a group of related tools that support different stages of the data analysis workflow.

Menu Purpose
Tableau Provides application-level options such as preferences, product activation, settings, and quitting Tableau.
File Used to create, open, save, export, and publish Tableau workbooks and data sources.
Data Contains tools for managing data connections, refreshing data, creating extracts, and editing data sources.
Worksheet Provides commands related to worksheet management such as creating new sheets, duplicating sheets, clearing views, and exporting worksheet data.
Dashboard Contains tools used to create and design dashboards, including adding objects, arranging layouts, and controlling dashboard behavior.
Story Provides functionality for building data stories, which present dashboards and worksheets in a sequential narrative format.
Analysis Includes analytical tools such as reference lines, trend lines, forecasting, clustering, and aggregation settings.
Map Provides geographic visualization tools such as map layers, background maps, geocoding, and spatial settings.
Format Controls formatting options including fonts, colors, shading, borders, alignment, and number formatting.
Server Used to publish dashboards and data sources to Tableau Server or Tableau Cloud, manage permissions, and update published content.
Window Allows users to manage Tableau windows, switch between views, and control layout settings.
Help Provides access to Tableau documentation, tutorials, product help, and support resources.

Tableau Interface Overview

The Tableau workspace contains several key components that help analysts explore data, build visualizations, and organize dashboards.

Each labeled section in the interface represents a group of tools used during the visualization process.

Tableau Interface
Label Section Description
A Data Pane Displays all available fields from the connected dataset.
B Columns and Rows Shelves Control how fields are arranged to build the visualization.
C Show Me Panel Suggests visualization types based on selected fields.
D Pages and Filters Area Controls navigation through data and restricts which data appears in the view.
E Worksheet Tabs Allows creation and navigation between worksheets, dashboards, and stories.
F Toolbar Provides quick access to commonly used commands and formatting tools.

A — Data Pane

The Data Pane contains all fields from the connected data source.

Fields are organized into several sections:

  • Dimensions – categorical fields used to group data
  • Measures – numerical fields used for calculations
  • Measure Names / Measure Values – system fields used for multi-measure visualizations
  • Generated fields – automatically created fields such as latitude and longitude

Additional tools within the Data Pane include:

  • Search bar – quickly locate fields in large datasets
  • Sort fields button – organize fields alphabetically or by type
  • Group and hierarchy options – create logical relationships between fields

The Data Pane is the starting point for building visualizations, since fields are dragged from this area into shelves and cards.

B — Columns and Rows Shelves

The Columns and Rows shelves control the structure of the visualization.

Tools within this section include:

  • Columns shelf – creates the horizontal axis of a chart
  • Rows shelf – creates the vertical axis of a chart
  • Field pills – represent the fields used in the visualization
  • Aggregation indicators – show functions such as SUM, AVG, or COUNT applied to measures
  • Drop zones – allow users to place additional fields to expand the visualization

These shelves define how data is arranged and determine the basic layout of the chart.

C — Show Me Panel

The Show Me panel provides a collection of visualization templates that Tableau can generate automatically.

Tools within this panel include icons for chart types.

When fields are selected in the Data Pane, compatible chart types become highlighted in the Show Me panel.

Selecting one of these icons automatically generates the corresponding visualization.

D — Pages, Filters, and Marks Area

This section contains tools used to control how data appears in the visualization.

Pages Shelf

  • Allows the visualization to be broken into multiple views
  • Enables step-by-step navigation through data categories
  • Often used for time-based exploration

Filters Shelf

  • Restricts which records are included in the visualization
  • Supports filtering by dimension values, measures, or date ranges
  • Filters can also be displayed as interactive controls on dashboards

Marks Card

The Marks card controls the visual appearance of data points.

Tools available in the Marks card include:

  • Color – changes color encoding of marks
  • Size – adjusts size of marks
  • Label – displays values as text on marks
  • Detail – adds additional granularity to the visualization
  • Tooltip – customizes information shown when hovering over marks

Tooltips

Tooltips are interactive labels that appear when a user hovers over a data point in a visualization.

They provide additional context without cluttering the chart.

Key characteristics of tooltips:

  • Display detailed information about a specific mark
  • Automatically include fields used in the visualization
  • Can be fully customized using text and dynamic fields
  • Support formatting and conditional logic

Typical uses of tooltips:

  • Showing exact values behind aggregated metrics
  • Providing additional dimensions not visible in the chart
  • Displaying calculated metrics or comparisons
  • Improving user understanding without adding visual complexity

To edit tooltips:

  1. Open the Marks card
  2. Click Tooltip
  3. Customize the content using inserted fields and text

Tooltips are essential for making dashboards more informative and interactive while keeping visuals clean.

E — Worksheet Tabs

The bottom section of the interface contains navigation tabs used to organize analytical work.

Tools within this section include:

  • Data Source tab – view and manage the connected dataset
  • Worksheet tabs – individual visualizations
  • New Worksheet button – create additional charts
  • New Dashboard button – combine multiple worksheets into a dashboard
  • New Story button – create sequential presentations of dashboards

These tabs help organize the analytical workflow inside a Tableau workbook.

F — Toolbar

The Toolbar provides quick-access buttons for common commands used while building visualizations.

Tools commonly available in the toolbar include:

  • Undo / Redo – reverse or repeat previous actions
  • Save – save the workbook
  • Sort Ascending / Descending – reorder values in a visualization
  • Swap Rows and Columns – quickly switch axes
  • Text tool – add annotations or titles
  • Format options – adjust visual formatting
  • Presentation mode – display the visualization in full-screen format
  • Pause automatic updates – temporarily stop queries while editing

These controls help analysts work more efficiently by providing shortcuts for frequent actions.

Connecting to Data Sources

Tableau supports connections to many types of data sources including:

  • Excel
  • CSV
  • Databases
  • Cloud platforms

For this session we connect to an Excel dataset.

Steps:

  1. Open Tableau Desktop
  2. Click Connect → Microsoft Excel
  3. Select airbnb.xlsx
  4. Drag the sheet into the workspace

Connect to Excel

Tableau Data Model Concepts

Understanding how Tableau interprets fields is essential for building correct visualizations.

Data Types

Tableau automatically assigns data types such as:

  • String (text)
  • Number (whole or decimal)
  • Date
  • Date & Time
  • Boolean
  • Geographic

Example fields from the Airbnb dataset:

Field Data Type
Name String
Neighbourhood String
Price Number
Beds Number
Host Since Date

Dimensions vs Measures

When Tableau loads a dataset, it automatically divides fields into Dimensions and Measures.

Understanding this distinction is critical because it determines how data is visualized.

  • Dimensions define categories
  • Measures define numeric values

In simple terms:

  • Dimensions answer “by what category?”
  • Measures answer “how much?” or “how many?”

Dimensions

Dimensions are fields that describe qualitative attributes of the data.

They are used to segment, group, or categorize records.

Typical characteristics of dimensions:

  • Often text or date fields
  • Used to organize the data into categories
  • Displayed as blue pills in Tableau
  • Often placed on Rows, Columns, Filters, or Color

Examples from the Airbnb dataset:

Field Description
Name Listing name
Neighbourhood Area of the listing
Property Type Apartment, house, loft
Room Type Entire home, private room
Zipcode Postal code

Example visualization:

Listings by Neighborhood

Steps:

  1. Drag Neighbourhood → Rows
  2. Drag Number of Records → Columns

Dimension

Measures

Measures represent quantitative values that can be calculated or aggregated.

Typical characteristics of measures:

  • Usually numeric fields
  • Aggregated automatically
  • Displayed as green pills
  • Create axes in charts

Examples from the Airbnb dataset:

Field Description
Price Nightly listing price
Beds Number of beds
Number Of Reviews Total reviews
Review Scores Rating Review score

Example visualization:

Average price of listings

Steps:

  1. Drag Price → Columns
  2. Right click and choose Measure → Average

Tableau automatically calculates:

AVG(Price)

Dimension

Aggregation of Measures

Measures are aggregated when used in visualizations.

Common aggregation functions include:

Function Purpose
SUM() Total value
AVG() Average value
COUNT() Number of records
COUNTD() Distinct values
MIN() Minimum value
MAX() Maximum value

Using Dimensions and Measures Together

Most visualizations combine dimensions and measures.

General rule:

Dimension → organizes the data
Measure → calculates numeric values

Example:

Average price by property type

Property Type Avg Price
Apartment 150
House 180
Loft 210

Discrete vs Continuous Fields

Fields in Tableau can behave as discrete or continuous.

Type Appearance Behavior
Discrete Blue pill Creates categories
Continuous Green pill Creates an axis

Example:

Field Behavior
Property Type Discrete
Price Continuous
Continuous Discrete
Continuous Discrete

Workbook Formatting

Workbook formatting controls the visual appearance and consistency of worksheets and dashboards.

Proper formatting improves readability, usability, and professional presentation.

Key formatting areas include:

  • Fonts – control text size, style, and hierarchy
  • Colors – define color palettes and highlight important data
  • Shading – adjust background colors of panes and headers
  • Borders – add separation between elements
  • Alignment – control positioning of text and labels
  • Number formatting – define how values are displayed (currency, percentages, decimals)

Formatting can be applied at multiple levels:

  • Worksheet level – affects a single visualization
  • Dashboard level – ensures consistency across multiple charts
  • Workbook level – applies global styling rules

Common best practices:

  • Use consistent fonts across all sheets
  • Apply a limited and meaningful color palette
  • Align elements for a clean layout
  • Avoid excessive gridlines and borders
  • Format numbers clearly (e.g., 1K, 1M, percentages)

Formatting tools can be accessed through:

  • Format menu in the Menu Bar
  • Right-click options within the visualization
  • Formatting pane inside Tableau

Proper workbook formatting ensures that dashboards are not only functional but also clear, consistent, and visually appealing.

Creating Basic Visualizations

Using the Airbnb dataset we can build several types of charts.

Bar Chart — Listings by Property Type

Question:

Which property is most common?

Steps:

  1. Drag Name → Columns
  2. Drag Number of Records → Rows
  3. Sort descending

Bar Chart

Line Chart — Listings Over Time

Question:

How did the number of hosts grow over time?

Steps:

  1. Drag Host Since → Columns
  2. Change to Month(Host Since)
  3. Drag Number of Records → Rows

Line Chart

Pie Chart — Property Type Distribution

Question:

What proportion of listings are apartments?

Steps:

  1. Change Marks type → Pie
  2. Drag Property Type → Color
  3. Drag Number of Records → Angle

Pie Chart

Scatter Plot — Price vs Reviews

Question:

Do more expensive listings receive more reviews?

Steps:

  1. Drag Price → Columns
  2. Drag Number Of Reviews → Rows
  3. Drag Property Type → Color

Scatter Plot

Adding Interactivity

One of the main strengths of Tableau is the ability to create interactive visualizations.
Interactivity allows users to explore data dynamically, rather than viewing static charts.

Instead of presenting a single fixed view, interactive dashboards allow users to:

  • Focus on specific categories or time periods
  • Drill into subsets of the data
  • Highlight important segments
  • Reorder and reorganize information

This makes dashboards much more useful for data exploration and decision-making.

Several Tableau features enable this interactivity.

Feature Purpose
Filters Restrict data displayed
Groups Combine categories
Sets Define subsets
Sorting Control order of values

Filters

Filters allow analysts to restrict which data is displayed in a visualization.

They help focus analysis on specific segments of the dataset.

For example, in the Airbnb dataset, a user might want to analyze:

  • Listings in a specific neighbourhood
  • Listings with price above a certain threshold
  • Listings from a specific year

Steps to create a filter:

  1. Drag a field to the Filters shelf
  2. Select which values to include
  3. Optionally show the filter on the dashboard

Example:

Filter listings by Neighbourhood

Neighbourhood = Bronx 
Neighbourhood = Brooklyn

Only listings from Bronx, Brooklyn will be displayed.

Filters are commonly used in dashboards to allow user-driven exploration.

Filters

Groups

Groups allow analysts to combine multiple dimension values into a single category.

This is useful when a dataset contains many small categories that should be analyzed together.

Example from the Airbnb dataset:

Several neighbourhoods can be combined into Boroughs:

Inner Boroughs, Outer Boroughs

Steps to create a group:

  1. Select multiple values in a dimension
  2. Right-click and choose Group
  3. Rename the group

Groups are helpful for:

  • Simplifying complex datasets
  • Aggregating small categories
  • Creating custom classification structures

Groups

Sets

Sets define a subset of data based on rules or manual selection.

Unlike groups, sets are often dynamic and can change based on conditions.

Examples of sets include:

  • Top 10 most expensive listings
  • Listings with more than 100 reviews
  • Top neighborhoods by average price

Sets are particularly useful for:

  • Highlighting important segments
  • Creating comparisons between groups
  • Supporting advanced calculations

Example:

Top 10 listings by Number Of Reviews

Tableau automatically calculates the subset.

Sets

Sorting

Sorting controls the order in which categories appear in a visualization.

Sorting improves readability and helps highlight patterns.

For example:

Instead of showing property types alphabetically:

Apartment
Bed & Breakfast
Boat

Sorting by number of listings will show:

Apartment
House
Loft

ordered from highest to lowest listing count.

Sorting options include:

  • Ascending
  • Descending
  • Sort by field value
  • Manual sorting

Sorting is especially useful in:

  • Bar charts
  • Ranked lists
  • Top-N analysis

Sorting

Why Interactivity Matters

Interactive dashboards allow users to move from static reporting to exploratory analysis.

Users can:

  • Filter the dataset
  • Focus on specific segments
  • Identify trends quickly
  • Explore different scenarios

This capability is one of the reasons Tableau is widely used for business intelligence and analytical dashboards.

Hands-On Task

Build a simple Tableau dashboard using the Airbnb dataset.

Steps:

  1. Connect to airbnb.xlsx
  2. Create at least three visualizations
  3. Add one interactive filter
  4. Combine worksheets into a dashboard
  5. Publish to Tableau Public

Articles

  1. https://public.tableau.com/en-us/s/resources
  2. https://public.tableau.com/app/profile/glowbyte.consulting/viz/ChartChooser_15550897459460/ChartChooser

Videos 1. Introduction to Tableau for Beginners

  1. https://www.youtube.com/watch?v=OmNeLFmyMJQ