How to Create a New Workbook in Tableau Desktop

Starting a new project in Tableau Desktop is the first step toward uncovering insights in your data. This guide will walk you through creating a new workbook, connecting to a data source, and building your first basic visualization. We'll skip the theory and jump directly into the practical steps you'll use every time you open the application.

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What Exactly is a Tableau Workbook?

Before creating one, it helps to know what it is. A Tableau workbook is the file where all of your work is saved. It contains your worksheets, dashboards, and stories. Think of it like a Microsoft Word document or an Excel spreadsheet file - it’s the container for everything you build.

You'll encounter two main types of workbook files, and understanding the difference is important for saving and sharing your work:

• Tableau Workbook (.twb): This file contains all the information about your worksheets and dashboards, including how your views are structured, the formatting, and the calculations you’ve created. It holds the instructions for how to generate visualizations from your data, but it does not contain the data itself. It maintains a live connection to your original data source. This makes the file size very small.
• Tableau Packaged Workbook (.twbx): This is an enhanced version of the workbook. It packages the original .twb file along with a copy of the data source file (like an Excel file or CSV) all into a single, zipped-up file. If you need to share your workbook with someone who doesn't have access to the original data file, you must use a .twbx.

For now, just know that a workbook is your project file. We'll decide which format to save it in later.

Step 1: Launch Tableau and Connect to Your Data

When you first open Tableau Desktop, you’re greeted by the Start Page. This screen is your launchpad for any new project. The main focus here is the Connect pane on the left side of the screen.

The Connect pane is organized by the type of data you want to connect to. You can connect to a wide variety of data sources, but they generally fall into two categories:

• To a File: This is for flat files stored locally on your computer or a network drive. Common options include Microsoft Excel, Text files (like .csv), JSON files, and statistical files like SAS or SPSS.
• To a Server: This is for data stored in a database or cloud platform. You'll see connectors for everything from Microsoft SQL Server and Oracle to cloud data warehouses like Snowflake, Google BigQuery, and Amazon Redshift.

For this tutorial, let's go through the most common starting point: connecting to an Excel file.

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Connecting to an Excel File

Follow these steps to connect your data:

1. With Tableau Desktop open on the Start Page, look at the Connect pane.
2. Under the "To a File" header, click on Microsoft Excel.
3. A file browser window will appear. Navigate to the location of your Excel file, select it, and click Open. (If you're brand new, you can find the "Sample - Superstore.xls" file in your My Tableau Repository/Datasources folder to follow along).

Once you select your file, Tableau will immediately process it and take you to the Data Source page.

Step 2: Get Familiar with the Data Source Page

The Data Source page is where you prepare your data for analysis. Here, you can combine tables, change data types, and preview your information before you start building charts. It might look a little technical at first, but it’s straightforward once you understand its three main areas.

1. The Left Pane (Connections)

On the far left, you'll see details about your connection. It shows the name of the file you connected to (e.g., "Sample - Superstore") and lists all the accessible sheets or tables within that file underneath. In our Excel example, you’ll see sheets named "Orders," "People," and "Returns."

2. The Canvas (Top Center)

This is the main area where you build your data source. You tell Tableau which tables you want to use for your analysis by dragging them from the left pane into this canvas area. For a simple analysis, you might just use one sheet.

• Drag the "Orders" sheet from the left pane and drop it into the canvas where it says, "Drag tables here."

If you were working with a database containing multiple tables that need to be joined together (for example, combining a Customers table with a Sales table), you would drag multiple tables onto the canvas and define the relationships between them using what Tableau calls "noodles."

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3. The Data Grid (Bottom)

Once you've dragged a table to the canvas, the bottom section of the screen will fill with a preview of your data. This grid shows your columns and rows, similar to how they look in Excel.

This area is incredibly useful for a quick check-up on your data before you build anything:

• Column Headers: You'll see the names of each field from your data source.
• Data Types: Above each column name is a small icon representing the data type Tableau has assigned. A # signifies a number, Abc means it's a string (text), and a small calendar indicates a date. You can click these icons to change the data type if Tableau guessed incorrectly.
• Data Preview: You can see the first 1,000 or so rows, allowing you to scroll through and spot any obvious issues or get a feel for the values.

After reviewing your data and seeing that everything looks correct, you are ready to move on. At the bottom of the application, click on the orange tab that says "Sheet 1."

Step 3: Build Your First Visualization in the Workspace

Clicking "Sheet 1" takes you to the heart of Tableau: the worksheet. This is your canvas for creating individual charts, maps, and tables. Let's break down the main components of this screen.

The Data Pane

On the left side of the screen is the Data pane. It lists all the columns from your data source, but it intelligently divides them into two distinct categories:

• Dimensions (Blue): These are categorical or descriptive fields. They are things you typically use to slice and dice your data. Examples include Customer Name, Product Category, and Region. Dimensions usually show up as blue "pills" when you drag them into the view.
• Measures (Green): These are numerical fields that you can perform mathematical operations on, like sum, average, or count. Examples include Sales, Profit, and Quantity. Measures usually show up as green "pills."

This separation of dimensions and measures is a fundamental concept in Tableau. Dimensions give your data context, measures provide the numbers.

The Shelves and the Marks Card

To build a visualization, you drag fields from the Data Pane onto various "shelves" or "cards" in the main workspace.

• Columns Shelf: Placing a field here will create columns in your table or chart.
• Rows Shelf: Placing a field here will create rows.
• Marks Card: This card controls the visual appearance of your data points (the "marks"). You can change their color, size, shape, and what text labels or tooltips appear.
• Filters Shelf: This is where you put fields to filter the data being shown in your visualization.

Example: Creating a Simple Bar Chart

Let's use these components to answer a simple business question: "What are our Sales for each Product Category?"

1. Drag Dimension to Columns: Find the Category field in the Data Pane under Dimensions. Click and drag it, dropping it onto the Columns shelf. You'll see three column headers appear in the main view: "Furniture," "Office Supplies," and "Technology."
2. Drag Measure to Rows: Now find the Sales field under Measures. Click and drag it onto the Rows shelf.

Just like that, Tableau generates a vertical bar chart. It automatically summed up the Sales for each Category and displayed the results visually. We now have a quick answer to our question.

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Enhancing the Visualization with the Marks Card

Our chart is good, but it could be better. Let’s add more context using the Marks Card.

• Add Color: What if we want to see which category is most profitable? Find the Profit measure in the Data pane and drag it onto the Color tile on the Marks Card. The bars instantly change color, reflecting a gradient where higher profit is a darker shade and lower profit is lighter (or even orange for negative profit).
• Add Labels: To see the exact sales figures on the bars, drag the Sales measure and drop it onto the Label tile on the Marks Card. The sum of sales now appears on top of each bar.

In just a few drags and drops, we've created a new workbook, connected to data, and built an insightful visualization that shows Sales by Category, colored by Profit.

Step 4: Save Your New Tableau Workbook

The final step is to save your hard work. Go to the top menu and select File > Save As...

A dialog box will open where you can name your file. Here, you'll need to make a critical choice at the "Save as type" dropdown:

• Choose Tableau Workbook (.twb) if you will always have access to the original Excel file on your computer, in the same location. This is good for saving drafts of your own work.
• Choose Tableau Packaged Workbook (.twbx) if you plan to share this workbook with a colleague, email it to someone, or open it on a different computer that does not have the original Sample - Superstore.xls file. This is the safest and most common option for sharing.

Pick a file type, give your workbook a name like "My First Sales Analysis," and click Save.

You’ve officially created, built, and saved your first Tableau workbook!

Final Thoughts

This walkthrough covered the fundamental process of creating a new workbook in Tableau Desktop - from the initial connection to a data source to building a visualization and saving your file. Mastering these foundational steps is the gateway to exploring all the powerful analytics and dashboarding features Tableau has to offer.

While Tableau is a fantastic tool, it does involve a learning curve of navigating shelves, cards, and data source panes. We built Graphed to simplify this workflow. Instead of dragging and dropping pills, you connect your data sources once and just ask for the viz you need in simple language - like "create a bar chart showing sales by category." We turn the process of building reports from a manual, multi-step task into a quick, conversational experience.