How to Create Visuals in Tableau

Creating compelling visuals from your data doesn’t have to be a monumental task. With Tableau, you can turn complex spreadsheets into clear, interactive charts and maps that tell a story. This guide will walk you through the fundamentals, from connecting your data to building your first essential visualizations.

First Things First: Connecting to Your Data

Before you can build anything, you need to bring your data into Tableau. The platform is designed to connect to an incredible variety of data sources, so whether your information lives in a simple Excel file or a complex SQL database, you're covered.

When you first open Tableau Desktop, you’ll be greeted with the "Connect" pane on the left side of the screen. Here’s how to get started:

• For file-based data: If you're working with files like Microsoft Excel, CSV, or Text files, simply click on the corresponding option under "To a File" and locate the file on your computer.
• For server-based data: If your data is in a database like PostgreSQL, MySQL, Amazon Redshift, or Google BigQuery, you'll choose the correct one under "To a Server." You'll then need to enter your server credentials (like server name, username, and password) to establish the connection.

Once you’re connected, Tableau will take you to the Data Source page. This screen gives you a preview of your data and lets you prepare it for analysis. You can drag and drop different tables to create relationships or joins, allowing you to blend data from multiple sources together into one unified view.

Understanding the Tableau Workspace

After you’ve connected your data, you’ll open a "worksheet" – this is your canvas for creating visuals. Understanding the main components of this workspace is the most important step in mastering Tableau.

Dimensions vs. Measures

In the "Data" pane on the left, Tableau automatically separates your data fields into two categories: Dimensions and Measures. Getting this concept down is paramount.

• Dimensions (Blue): These are your qualitative, categorical fields. Think of them as the things you want to slice and dice your data by. Examples include dates, customer names, geographic regions, or product categories. They are represented by blue pills in the workspace.
• Measures (Green): These are your quantitative, numerical fields - the numbers you want to analyze. Examples include sales, profit, quantity, or website sessions. They are represented by green pills in the workspace, and Tableau automatically aggregates them (e.g., SUM, AVG, MAX).

Shelves and Cards

The main part of your worksheet is where you’ll drag and drop these "pills" to build your visual.

• Columns and Rows Shelves: These are at the top and side of the workspace. You drop fields here to create the X and Y axes of your chart. Placing a dimension on the Columns shelf and a measure on the Rows shelf is the classic way to create a bar chart.
• The Marks Card: This powerful little box controls the visual appearance of the data points, or "marks," in a chart. It contains several properties you can use:

How to Build an Essential Bar Chart

The bar chart is the foundation of data visualization. It's perfect for comparing categories. Let's build one to show Sales by Product Category.

1. Find the Category dimension in your Data pane. Click and drag it up to the Columns shelf. You'll see column headers appear for each of your product categories (e.g., Furniture, Office Supplies, Technology).
2. Next, find the Sales measure. Click and drag it to the Rows shelf.

That's it! Tableau immediately generates a vertical bar chart. The height of each bar represents the total sales for each category. For a bit more detail, try these additions:

• Drag the Sales measure again, but this time drop it onto the Label property in the Marks card. The exact sales number will now appear on each bar.
• Drag the Region dimension to the Color property in the Marks card. Your bar chart will now be a stacked bar chart, showing you the proportion of sales from each region within each category.

How to Create a Line Chart for Trend Analysis

Line charts are the best way to visualize how a measure changes over time. They are perfect for identifying trends, seasonality, or unexpected spikes. Let's track Sales over Time.

1. Find a date dimension like Order Date and drag it to the Columns shelf. Tableau will likely default to showing SUM(Sales) for each year.
2. Drag the Sales measure to the Rows shelf. A line chart will appear, connecting the total sales values for each year.

Often, you’ll want to see more detail than just the year. You can change the date granularity with a single click:

• Right-click the blue 'YEAR(Order Date)' pill on the Columns shelf.
• In the menu that appears, you can change it to Quarter, Month, Week, or a continuous monthly trend line. Choosing "Month" under the second section of the menu will give you a continuous line showing sales performance month-over-month across all years.

How to Make Insightful Maps

Maps are one of Tableau's star features, instantly turning geographic data into a visually compelling and easy-to-understand format. If your data contains fields like city, state, postal code, or country, Tableau will recognize them automatically.

Let's map our Sales by State.

1. Find a geographic dimension like State in the Data pane. You’ll notice a small globe icon next to it.
2. Simply double-click the State dimension. Tableau will automatically generate a map with a dot placed in each state where you have data.
3. Right now, the map just shows locations. Let's make it more meaningful. Drag the Sales measure and drop it onto the Color property in the Marks card.

The map is now a choropleth, or "filled map," where each state is color-coded by its total sales. The states with higher sales will be a darker shade, instantly showing you where your top markets are.

Want to layer on more information? Try dragging the Profit measure onto the Size property. Now, the size of the mark for each state is determined by its profitability.

How to Analyze Relationships with a Scatter Plot

Scatter plots are fantastic for understanding the relationship, or correlation, between two different measures. Are sales and profit related? Does a discount given correlate with the quantity sold?

Let's build a scatter plot to analyze Sales vs. Profit for individual orders.

1. Drag the Sales measure to the Columns shelf.
2. Drag the Profit measure to the Rows shelf. Right now, you'll only see a single mark in your view. This is because Tableau has aggregated all sales and all profits into a single point.
3. To see the relationship for each individual product or customer, we need to add more detail. Drag the Customer Name or Product Name dimension and drop it onto the Detail property in the Marks card.

Now, your view is populated with a "scatter" of marks, where each mark represents a customer. This allows you to quickly spot outliers — for example, high-sales customers who are actually unprofitable. To make the correlation even clearer, you can switch to the "Analytics" pane and drag a "Trend Line" onto the view.

Final Thoughts

Getting comfortable in Tableau is all about understanding the difference between dimensions and measures and how to use them on the various shelves and cards to build insights. By starting with fundamental visuals like bar charts, line charts, maps, and scatter plots, you gain a powerful toolkit for transforming raw data into clear, actionable information.

Learning business intelligence tools like Tableau is a huge advantage, but sometimes the biggest challenge isn’t building the chart — it's having the time to connect all your data and sift through it for answers. We built Graphed to short-circuit that entire process. Instead of spending hours wrangling data and dragging and dropping pills, you can connect your marketing and sales sources in one click and then just describe the charts and dashboards you need in plain English. This turns what would be hours of manual reporting work into a simple, 30-second conversation.