When to Use Which Chart in Tableau?

Choosing the right chart in Tableau can transform a confusing spreadsheet into a clear insight, but staring at the "Show Me" panel can feel like a pop quiz. This guide will walk you through the most common Tableau chart types and explain exactly when and why you should use each one, giving you the confidence to visualize your data effectively.

Start With Your Goal: What Question Are You Asking?

Before you drag a single field onto the canvas, ask yourself one simple question: "What do I want to show?" The best chart is always the one that answers your question most clearly. Most data questions fall into a few key categories:

• Comparing values between different categories
• Showing how different parts make up a whole
• Tracking changes over a period of time
• Understanding the relationship between variables
• Visualizing geographical data
• Showing how data is distributed

Let's break down the best charts for each of these goals.

1. Charts for Comparing Values

When you need to see how one category stacks up against another, comparison charts are your best friend. They are arguably the most common and easily understood visualizations.

Bar and Column Charts

The humble bar chart is the workhorse of data visualization. It's simple, intuitive, and incredibly effective at comparing values across different categories.

• When to use them: Use a bar or column chart when you have one numerical measure you want to compare across several distinct categories.
• Vertical (Column) vs. Horizontal (Bar):

Example: You want to see which marketing channels are driving the most website traffic. A horizontal bar chart is perfect. The channels (Organic Search, Paid Social, Email, etc.) are your categories, and the number of sessions is your numerical measure. Sorting the bars from highest to lowest makes it instantly obvious which channels are your top performers.

Pro Tip: Always sort your bars in a logical order (usually descending or ascending) unless the categories have a natural order of their own (like months of the year).

Bullet Graphs

A bullet graph is a supercharged bar chart. It takes a standard comparison and adds context by plotting a measure against a target.

• When to use it: Use a bullet graph when you need to track performance against a specific goal. It's a staple in performance dashboards.
• How it works: It typically shows a single bar representing the actual value, a marker line representing the target value, and shaded bands in the background representing performance ranges (like poor, average, good).

Example: Your sales team needs to track their quarterly performance. A dashboard of bullet graphs could show each sales rep’s current revenue (the bar) compared to their quarterly quota (the target line). You can immediately see who is on track, who has met their goal, and who is falling behind.

2. Charts for Showing Parts of a Whole

Sometimes the key insight isn't the total number, but how that total is broken down. Composition charts show the anatomy of your data.

Pie and Donut Charts

Pie charts get a bad rap in the data viz world, and often for good reason. Our brains aren't great at comparing the sizes of angles, making it difficult to judge the relative proportions of slices. However, they can be effective in a few specific situations.

• When to use them: Use a pie or donut chart only when you want to show the relative proportions of a handful of categories that add up to a meaningful 100%. Don't use more than 5-6 slices.
• The Golden Rule: If the primary goal is to compare the categories to each other, use a bar chart instead. If the goal is to show one or two huge slices dominating the whole, a pie chart can work.

Example: You want a quick visual of market share on your dashboard's homepage. A pie chart showing your company's share vs. your top two competitors and "Other" makes the point quickly and visually.

Treemaps

A treemap is an excellent, modern alternative to the pie chart, especially when you have hierarchical data or a lot of categories.

• When to use it: Use a treemap to show parts-of-a-whole where you need to visualize two levels of data (a category and a sub-category) simultaneously, or when you have too many categories for a bar chart or pie chart.
• How it works: Treemaps use nested rectangles where the size of each rectangle represents its value. You can use color to represent a second measure or to group related categories.

Example: An e-commerce manager wants to see a breakdown of sales. A treemap could use large rectangles to represent product categories (e.g., Electronics, Apparel, Home Goods). Within each large rectangle, smaller rectangles could represent individual products, with their size corresponding to sales volume. This gives a rich, at-a-glance view of which categories — and which specific products — are the biggest drivers of revenue.

3. Charts for Tracking Changes Over Time

Is performance going up, down, or staying flat? Time-series charts are essential for spotting trends, seasonality, and unusual spikes or dips in your data.

Line Charts

The line chart is the go-to choice for visualizing a continuous data set over a period of time. It’s perfect for showing trends.

• When to use it: Use a line chart whenever you have a date or time dimension on your horizontal axis and a continuous numerical measure on your vertical axis.

Example: You want to track daily website sessions for the last 90 days. Plotting the date on the x-axis and total sessions on the y-axis will create a line chart that clearly shows your traffic trends, the impact of marketing campaigns, and any weekly patterns (like traffic dipping on weekends).

Area Charts

An area chart is essentially a line chart with the space between the line and the x-axis filled in. This helps emphasize the volume or magnitude of change over time.

• When to use it: Use a standard area chart for the same reasons you'd use a line chart, but when you want to draw more attention to the total volume.
• Stacked Area Charts: These are particularly useful for showing how a part-to-whole relationship has changed over time. Be cautious, though — they can be misleading if the user is interested in the trend of the upper segments, which don't have a stable baseline.

Example: A SaaS company wants to see how its revenue composition (e.g., from Subscription, Services, and Other) has evolved over the past two years. A stacked area chart can show not only the growth in total revenue but also how the contribution from each revenue stream has shifted over that period.

4. Charts for Understanding Relationships

Sometimes you need to see how two different variables interact. Is more of one thing related to more (or less) of another?

Scatter Plots

A scatter plot is the ideal field for visualizing the relationship, or correlation, between two different numerical variables.

• When to use it: Use a scatter plot when you have two numerical measures for each dimension member and you want to see if a pattern emerges.
• How it works: Each point on the chart represents one item (like a customer, product, or day) plotted according to its value on both axes. Patterns can reveal positive correlation (points trend up and to the right), negative correlation (down and to the right), or no correlation (points are scattered randomly).

Example: A marketing manager wants to know if there's a relationship between the amount spent on a paid search campaign and the revenue it generates. Plotting a point for each campaign with ad spend on the x-axis and revenue on the y-axis will quickly reveal whether higher spending generally leads to higher revenue. You can also easily spot outliers — campaigns that were highly profitable or ones that were a complete waste of money.

5. Charts for Visualizing Geographical Data

When "where" matters, nothing tells the story better than a map. Tableau is especially strong at creating rich, interactive maps.

Maps (Symbol and Filled)

Tableau can automatically create maps when it recognizes geographic data like countries, states, cities, or zip codes.

• When to use them: Use a map whenever location is a critical dimension in your data. It helps reveal regional patterns, hotspots, and geographic concentrations.
• Symbol vs. Filled:

Example: A national retailer wants to understand their performance across the country. A filled map coloring each state by its total sales can quickly show top-performing regions. Clicking on a state could then reveal a symbol map of individual store locations within that state, with bubble size indicating each store's profitability.

6. Charts for Showing Distribution

Distribution charts help you understand the spread and frequency of your data. Where does the data cluster? Are there any outliers?

Histograms

A histogram looks like a bar chart, but it's used to show the distribution of a single continuous numeric variable instead of comparing categories.

• When to use it: Use a histogram to understand how your data is distributed. It's great for seeing how frequently different values (or ranges of values) occur.
• How it works: Tableau takes a measure (like Sales Per Order), bins the values into ranges (e.g., $0-10, $11-20, $21-30), and then counts how many records fall into each bin.

Example: An online store wants to understand customer purchase behavior. A histogram of order value can show that most purchases are in the $40-60 range, with a long tail of fewer, higher-value purchases. This can inform marketing strategies and shipping fee thresholds.

Final Thoughts

Mastering chart selection in Tableau isn't about memorizing rules, it's about thinking clearly about the question you want to answer and choosing the visualization that makes that answer as obvious as possible. By starting with your goal, you can quickly narrow down your options and build dashboards that truly inform and drive action.

At Graphed, we’ve found that the biggest hurdle isn't always knowing which chart to use, but the time it takes to connect your data and build it. We designed our platform so you can get powerful visualizations without the steep learning curve. Instead of dragging fields and configuring settings in a complex tool, you can simply ask for "a line chart of our monthly revenue from Shopify" or "a breakdown of our Facebook Ads spend vs. revenue by campaign," and the dashboard is created for you in seconds. If you're looking to get insights from your apps without the reporting headaches, you might find Graphed a much faster way to find your answers.