What Chart to Use in Tableau?

Choosing the right chart in Tableau can feel like the hardest part of building a dashboard, but it doesn't have to be. The secret isn't memorizing dozens of chart types, but learning to ask the right question first. This guide will walk you through a simple framework for picking the perfect Tableau visualization based on the story you want your data to tell.

Start with Your Question, Not the Chart

Opening Tableau and facing an empty canvas can be intimidating. The "Show Me" panel presents a grid of options, but which one is right? Before you drag a single pill onto the shelf, stop and ask yourself one simple question: "What do I want to show?"

The chart is just the final expression of your insight. The real work is defining what you're trying to communicate. Are you comparing sales figures between regions? Tracking website traffic over the past year? Or trying to see if there's a relationship between ad spend and conversions? Your answer will immediately eliminate most chart types and point you directly to the best one for the job.

Think of it this way: a chart is a tool for answering a business question. If you don't know the question, you can't pick the right tool.

Showing Comparisons and Rankings

One of the most common tasks in data analysis is comparing values against each other. How does one category stack up against another? Which product is our top performer? Who is the leading salesperson? When your question involves words like greater than, less than, or ranked, you're dealing with comparisons.

Bar Charts (Your Go-To for Comparisons)

The bar chart is the undisputed champion of comparisons. Our brains are incredibly good at comparing the lengths of bars, making it easy to see at a glance which values are larger or smaller. They are simple, clear, and difficult to misinterpret.

• When to use it: Use a bar chart any time you want to compare a metric across different categories.
• Vertical Bars (Column Charts): These work best when you have a smaller number of categories (typically fewer than 10-12). They are great for showing things like revenue by product category or new customers by marketing channel.
• Horizontal Bars: If you have long category labels or many categories to compare, horizontal bars are your best friend. They prevent cluttered, unreadable axis labels and offer a clean, scannable view. They are perfect for ranking leaderboards, like "Top 20 Blog Posts by Page Views."

Example: You want to see which of your a-la-carte services generated the most revenue last quarter. A vertical bar chart with "Service Name" on the X-axis and "Sum of Revenue" on the Y-axis is the perfect visualization.

Side-by-Side Bar Charts

What if you want to add another layer to your comparison? A side-by-side (or clustered) bar chart lets you compare categories across another dimension. It places two or more bars next to each other for each category, making direct comparisons simple.

• When to use it: When you need to compare subgroups within a main category.

Example: You want to compare the sales performance of each product category for this year versus last year. A side-by-side bar chart would show you a bar for 2023 and a bar for 2024 for each product category, making it instantly clear which categories grew and which ones declined.

Bullet Graphs

A bullet graph is a super-powered bar chart that's perfect for measuring performance against a goal. It packs a lot of context into a small space by showing a primary measure (like current revenue) and comparing it to a target measure (like the sales quota).

• When to use it: To track progress toward a specific number or goal. It’s a great replacement for dashboard gauges and meters.

Example: You want to visualize how each of your sales reps is performing against their quarterly quota. A bullet graph for each rep would show their current sales as a bar, with a line or marker indicating their quota.

Tracking Trends Over Time

Another major business question is "how has this metric changed over a period of time?" Analyzing trends helps you understand performance, spot seasonal patterns, and make forecasts. When your question involves words like trend, growth, change, or over time, you need a time-series visualization.

Line Charts (The Classic for Time-Series Data)

A line chart is the standard for visualizing how a continuous metric changes over time. By connecting individual data points, it clearly shows the direction and magnitude of change, making it easy to spot trends, seasonality, or anomalies.

• When to use it: To track a continuous metric over a period (days, weeks, months, years).

Example: You want to track your website's total user sessions each month for the last year. A line chart with "Month" on the X-axis and "Sum of Sessions" on the Y-axis would instantly reveal growth trends or seasonal dips.

Area Charts

An area chart is a line chart with the space between the line and the x-axis filled in with color. This helps emphasize volume and magnitude over time. A stacked area chart can also show how the composition of a total has changed over time.

• When to use it: To show the volume of change over time or to visualize part-to-whole relationships over time.

Example: You want to see not just your total website traffic over time, but how much of that traffic came from different sources (Organic, Paid, Social). A stacked area chart could show the total traffic volume while also visualizing the proportion that each channel contributed each month.

Understanding Relationships and Correlation

Sometimes you need to know if two different variables are related to each other. Does increasing marketing spend lead to more sales? Is there a connection between a customer's discount rate and their lifetime value? These questions are about relationships and correlation.

Scatter Plots

A scatter plot is the go-to chart for visualizing the relationship between two numerical variables. Each dot on the chart represents one data point plotted at the intersection of its X and Y values. The resulting pattern of dots tells you what kind of relationship exists: positive, negative, or none.

• When to use it: When you want to see if two different measures are correlated.

Example: To determine if your advertising budget impacts sales, you could create a scatter plot with "Daily Ad Spend" on the X-axis and "Daily Revenue" on the Y-axis. If the dots trend upwards from left to right, it's a sign of a positive correlation.

Analyzing Parts of a Whole

"What makes up this total?" "What percentage of our audience came from this channel?" Questions about composition (or "part-to-whole") are common, but they have some of the most misused charts associated with them.

Pie Charts and Donut Charts (Use Sparingly)

Pie charts get a bad rap, and often for good reason. They are difficult to read accurately because people are not good at comparing angles and area. However, they can be effective in one specific scenario: showing the composition of a total when you have very few categories (ideally 2-4).

• When to use it: To show the percentage breakdown of a total with a small number of categories that add up to 100%.
• Pro Tip: More often than not, a simple bar chart is clearer and easier to interpret than a pie chart. If you must use one, always label it with percentages or raw numbers.

Example: Presenting survey results for a "Yes/No/Maybe" question is a reasonable use case for a pie chart.

Treemaps

A treemap is a fantastic way to display hierarchical data as a set of nested rectangles. The size of each rectangle represents one measure, while the color can represent a second measure. They are great for visualizing a part-to-whole relationship when you have a lot of categories that would make a bar or pie chart unreadable.

• When to use it: To visualize a large number of components that make up a whole, especially if there is a hierarchy.

Example: You want to see which product sub-categories contribute the most to your total sales. A treemap could show your main product categories as large rectangles, with smaller rectangles inside representing the sub-categories, sized by their sales contribution.

Visualizing Geographic Data

When the location of your data is important, a map is the obvious answer. Questions like "which states generate the most revenue?" or "where are our customers located?" require a geographic visualization.

Map Charts

Tableau makes creating map charts incredibly simple. If your data has geographic fields like country, state, city, or zip code, you can easily plot your data onto a map.

• Symbol Maps: Place a dot or symbol on the map at a specific location, with the size or color of the symbol representing a metric. Perfect for plotting individual store locations, with the dot size representing sales volume.
• Filled Maps (Choropleth Maps): Color-code geographic areas (like states or countries) based on a metric. Excellent for showing regional performance, like sales revenue by state.

Example: To identify top-performing sales regions, you could create a filled map of the United States where each state is color-coded by its total profit.

Final Thoughts

In the end, choosing the right visualization in Tableau comes back to the question you are trying to answer. By starting with a clear question - whether it’s about comparison, time, relationships, or composition - you can confidently select a chart type that makes your data clear, insightful, and actionable for your audience.

And while becoming proficient in a tool like Tableau is an incredibly valuable skill, we also know that there’s a steep learning curve to get started. Sometimes, the goal isn't to become a BI expert, but to get a quick, accurate answer to your business questions. For that, we created Graphed, where you can connect your data sources and simply ask questions in plain English. Instead of building vizzes manually, you can just ask, "Show me US Traffic versus Canada traffic as a line chart," and have a fully interactive, live dashboard created for you in seconds.