How to View Data in Tableau

Building a powerful visualization in Tableau feels great, but trusting the numbers behind it is even more important. Knowing how to quickly peek at the raw data that feeds your charts is a fundamental skill for any analyst. This guide will walk you through the various ways to view, inspect, and interact with the underlying data in your Tableau projects, so you can build with confidence and answer any question that comes your way.

Start at the Source: The Data Source Page

Your first encounter with your data in Tableau happens on the Data Source page. This is your initial staging area, where you connect to your files or databases and prepare them for analysis. Think of it as your preview window before you start creating charts.

What You'll See

When you connect to a data source, you'll see a screen divided into a few key areas:

• Left Pane (Connections & Tables): On the far left, you'll see your current data connection. If your source contains multiple tables (like an Excel file with multiple sheets or a database with many tables), they'll be listed here. You can drag and drop tables into the canvas to join them together.
• Top Pane (The Canvas): This is the main area where you build your data model. By dragging tables here, you can create relationships and joins between them. For a simple spreadsheet, you might only see one table in this canvas.
• Bottom Pane (The Data Grid): Below the canvas, you get a preview of your data's structure. This grid displays the columns (fields) and the first 1,000 rows of an extract (or sample if it's a Live connection). This is your first opportunity to do a "gut check" on your data.

Key Actions on the Data Source Page

Before you even move to a worksheet, this page lets you perform crucial data prep tasks:

• Review Column Headers: Do the names make sense? You can double-click any column header to rename it to something more intuitive (e.g., renaming CUST_ID to Customer ID).
• Check Data Types: Tableau is smart, but sometimes it gets data types wrong. A common issue is a column of ZIP codes being interpreted as a number (when it should be a string to preserve leading zeros) or dates being seen as text. Click the icon next to the column name (e.g., # for number, Abc for string) to change the data type.
• Get a Data Snapshot: Scrolling through the first few hundred rows gives you a feel for your dataset. Are there obvious nulls? Does the formatting look consistent? Catching these issues early saves headaches later.

The "View Data" Feature: Your Quick Inspection Tool

Once you’re in the worksheet view, the fastest and most common way to see the raw table of data behind any of your sources is the “View Data” option. This is perfect for when you need a comprehensive look at an entire data source without applying any filters or aggregations from your viz.

How to Access It

In the Data pane (the left-hand sidebar where your dimensions and measures are listed), simply right-click on the data source you want to inspect. A context menu will appear. From this menu, select "View Data."

A new window will pop up, displaying all the columns and rows for that source. By default, it shows a limited number of rows to keep things snappy, but you can specify a larger number to fetch more records.

When to Use It

The "View Data" option is incredibly useful for:

• Initial Verification: Before you build a single chart, you can scan the table to confirm that columns like Order Date are showing proper dates, sales figures are numbers, and customer names look correct.
• Copying Raw Data: Need a small sample of your data for documentation or a quick test in a spreadsheet? You can highlight the rows and columns in the "View Data" window and copy them directly to your clipboard.
• Troubleshooting Joins: If you've joined multiple tables, the "View Data" window shows the final, combined result. It's a perfect way to spot if your join is creating duplicate rows or unexpected null values where data didn't match up.

Diving Deeper: Viewing Data from a Visualization

This is where Tableau’s data inspection capabilities truly shine. A common analytics workflow involves noticing something interesting in a chart - a spike, a dip, or an outlier - and needing to investigate the specific data points that created it. Tableau lets you do this directly from any mark on your visualization.

How it Works

1. Click on a specific mark on your chart. This could be a bar in a bar chart, a point on a line graph, a state on a map, or a slice of a pie chart.
2. Hover over it to bring up the tooltip.
3. In the tooltip, you'll see a small icon that looks like a table (it's often named "View Data"). Click it.

This action opens a dialog box with two powerful tabs: Summary and Full Data (sometimes called "Underlying Data").

Understanding the Summary vs. Full Data Tabs

The Summary Tab

The Summary tab shows you the aggregated data that was used to draw the mark you selected. It only displays the dimensions and measures currently in your view.

Example: You have a bar chart showing SUM(Sales) by Region. The Region dimension is on Columns, and SUM(Sales) is on Rows. If you click on the "West" bar, the Summary tab will show you a single row:

• Region: West
• SUM(Sales): $725,458

This confirms the aggregated value for that specific bar. It’s a direct representation of what’s plotted.

The Full Data / Underlying Tab

The Full Data tab shows you every single individual row from your original data source that contributes to the mark you selected. It includes all fields from your data source, not just the ones in your visualization.

Example (continued): Using the same bar chart, if you click the "West" bar and then go to the "Full Data" tab, you won't see one row. Instead, you'll see every single transaction that occurred in the West region. You'd see columns like Order ID, Customer Name, Product Name, Order Date, and Sales for each of the thousands of individual sales that were summed up to create that bar.

Being able to toggle between the summarized view and the raw, line-item detail is essential for true data analysis. It's how you move from "what happened?" (the bar chart) to "why did it happen?" (the underlying transactions).

Building a Crosstab (Text Table) for Detailed Views

Sometimes, inspecting a window of data isn't enough. Your stakeholders might ask, "This chart is great, but can I just see all the numbers in a table?" In these cases, you can build a crosstab, which is just Tableau's name for a text table or pivot table.

This method doesn't just show you data, it allows you to organize it into a familiar spreadsheet-like format, making it easy for others to consume.

How to Create a Crosstab

1. Drag Dimensions to Rows and Columns: Start by dragging the fields you want to group by onto the Rows and Columns shelves. For example, drag Category to Rows and YEAR(Order Date) to Columns.
2. Add Measures to the View: Next, drag the measure you want to display, like Sales, and drop it onto the Text square on the mark's Card.
3. Format as Needed: You will now see a table of sales broken down by category for each year. You can add more dimensions to Rows or Columns to create more granular breakouts and use the formatting options to adjust fonts, colors, and number formats.

Once your crosstab is built, you can easily export it for others. Simply navigate to Worksheet > Export > Crosstab to Excel. This generates a perfectly formatted spreadsheet in one click, satisfying one of the most common requests in business reporting.

Bonus Tip: Use the Data Highlighter

While not a raw data view, the Data Highlighter is an invaluable tool for visually isolating related data across your dashboard.

To use it, find a dimension in your view (often shown as a color legend or filter). Click the dropdown arrow on that card and select "Show Highlighter." Now, when you hover over an item in the highlighter - like "Technology" in a Category highlighter - all marks related to the Technology category will instantly be highlighted across every chart on your dashboard, while everything else fades into the background.

This helps you see connections and patterns without having to filter out data, providing a more fluid and interactive way to explore and understand your information.

Final Thoughts

Mastering how to view data in Tableau is about building confidence in your analysis. From the initial review on the Data Source page to deep-diving into the raw records behind a single bar chart, these skills enable you to verify your numbers, answer follow-up questions, and ultimately, create dashboards that people trust.

Learning to navigate complex data views in powerful tools like Tableau is an essential skill, but the initial setup and learning curve can be steep for many. At Graphed, we believe that you shouldn’t need to be a data specialist to get answers about your business. We built Graphed to connect to your marketing and sales sources in seconds and let you build reports and dashboards with simple, natural language. It turns hours of manual analysis and dashboard configuration into a quick, intuitive conversation.