What Are Vizzes in Tableau?

If you're starting with Tableau, you'll hear the term "viz" mentioned constantly. A viz is simply shorthand for "visualization," and it’s the fundamental building block of everything you create in Tableau. This article breaks down what vizzes are, why they matter, and how you can start building them to turn raw data into clear, actionable insights.

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What Exactly Is a Viz?

In Tableau, a viz refers to any single chart, graph, map, or table you create on a worksheet. It is the visual representation of your data. Think of it this way: if your data source, like an Excel spreadsheet or a database, is the long list of raw ingredients, a viz is the finished dish that presents those ingredients in an understandable and appealing way.

A single viz could be a bar chart showing sales per product category, a line chart tracking website traffic over time, or a map highlighting customer locations by state. The goal of any viz is to communicate information visually, making it far easier to spot patterns, trends, relationships, and outliers than by looking at rows and columns of numbers.

Later on, you can combine multiple individual vizzes into a single, interactive dashboard, or arrange them sequentially to tell a story with your data. But it all starts with mastering the single viz.

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Choose Your Viz: Common Types of Visualizations in Tableau

Tableau’s power lies in its flexibility. It offers a wide variety of visualization types, and knowing which one to use for your specific data and question is the first step toward effective analysis. Tableau's "Show Me" feature is a great assistant, suggesting appropriate chart types based on the data you select.

Here are some of the most common and useful vizzes you’ll build:

1. Bar Charts

Bar charts are arguably the most common viz type, and for good reason - they are excellent for comparing categorical data. The length of each bar represents a value, making it instantly clear which category is largest, smallest, or how they rank against each other.

• When to use it: Comparing values across different categories. For example, comparing sales revenue for different product lines, marketing campaign performance, or support tickets by agent.
• Example: A chart showing total sales for four regions: North, South, East, and West. Readers can immediately see which region is the top performer.

2. Line Charts

Line charts are the best way to visualize change over a continuous period. By connecting data points with a line, they clearly illustrate trends, acceleration, or volatility over time.

• When to use it: Tracking a metric over a period like days, months, quarters, or years. Perfect for website sessions, monthly sales figures, stock prices, or temperature changes.
• Example: A line chart plotting your company’s monthly recurring revenue (MRR) over the last two years. This helps you quickly see growth trends and seasonality.

3. Pie Charts

Pie charts are used to show the proportions or percentages of a whole. Each slice represents a category, and the size of the slice corresponds to its percentage of the total. While popular, they can be misleading if used with too many categories.

• When to use it: Showing parts of a whole when you have only a few categories (ideally fewer than five). Think market share breakdown or budget allocation.
• Example: A chart showing the percentage breakdown of website traffic sources: Organic Search, Direct, Referral, and Social Media.

4. Scatter Plots

Scatter plots are ideal for exploring the relationship between two different numerical variables. Each dot on the plot represents a single data point, with its position determined by its values on the horizontal (X-axis) and vertical (Y-axis) axes.

• When to use it: Investigating if two variables are correlated. For example, is there a relationship between advertising spend and sales? Or between a student's study hours and their exam score?
• Example: A scatter plot with marketing spend on the X-axis and revenue on the Y-axis. You might see the data points cluster in a way that suggests that as spend increases, so does revenue.

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5. Maps

Whenever your data includes geographic information like countries, states, cities, or postal codes, maps are an impactful way to visualize it. Tableau can automatically recognize geographic data and plot it on a map.

• When to use it: Analyzing sales by territory, customer density, or any data with a spatial component.
• Example: A map of the United States with each state colored based on its total sales volume, giving you a quick visual understanding of your strongest and weakest markets.

6. Heat Maps

Heat maps use color to represent the magnitude or density of data points in a two-dimensional space. The intensity of the color helps you quickly identify areas of high and low concentration.

• When to use it: Comparing performance across many categories and sub-categories, such as identifying the most popular products on the busiest days of the week, or visualizing where users click on a webpage.
• Example: A grid showing products on one axis and months on the other, where each cell is colored based on sales volume - dark green for high sales, light green for low sales.

How to Build Your First Viz in Tableau (A Simple Walkthrough)

Let’s walk through the process of creating a simple viz. We'll build a classic bar chart to see which sub-categories are driving the most sales, using Tableau's sample Superstore dataset.

Step 1: Connect to Your Data

When you open Tableau, the first screen prompts you to connect to a data source. Tableau can connect to almost anything, from a simple Excel file to a complex SQL database. For this example, we’ll use the Sample - Superstore dataset that comes with Tableau. Simply find it under "Saved Data Sources" on the left pane and click on it.

Step 2: Understand the Workspace

Once you’re in a new worksheet, take a moment to look at the layout:

• Data Pane (Left): This is where your data fields are listed. Tableau automatically classifies them into Dimensions (categorical data like 'Category' or 'Region') and Measures (numerical data like 'Sales' or 'Profit').
• Shelves (Top): The most important shelves are Columns and Rows. This is where you will drag your data fields to build the viz.
• Marks Card (Middle Left): This allows you to control the visual properties of your viz, such as color, size, text labels, and chart type.
• Canvas (Center): The large empty space where your viz will appear.

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Step 3: Drag and Drop Your Fields

This is where the magic happens. To build our bar chart of Sales by Sub-Category:

1. Find the Sales measure in the Data pane. Click and drag it onto the Rows shelf. You'll see Tableau create a single vertical bar representing the total sum of sales.
2. Next, find the Sub-Category dimension. Click and drag it onto the Columns shelf.

Instantly, Tableau updates the canvas. You'll now see a bar chart with each sub-category along the bottom (X-axis) and the height of the bar representing its total sales (Y-axis).

That’s it! You've successfully built your first viz.

Step 4: Customize and Refine Your Viz

Now, let's make it more informative using the Marks card and some simple formatting.

• Add Color: To make profit levels stand out, find the Profit measure and drag it to the Color button on the Marks card. Your bars will now be colored based on their profitability, usually with a diverging color scheme like blue for positive profit and orange for negative.
• Sort Your Data: To easily see the top-performing sub-categories, you can sort the bars. Hover over the Sales axis title and a small sort icon will appear. Clicking this will sort the bars in descending or ascending order.
• Add Labels: To show the exact sales numbers, drag the Sales measure again, this time dropping it onto the Label button on the Marks Card. The sales value will now appear on each bar.

Tips for Creating Effective Vizzes

Building a viz is half the battle, building a good viz is what leads to real insight. Keep these principles in mind:

• Keep It Simple: Avoid overwhelming your audience. Each viz should have one clear purpose. Don't try to cram too much information into a single chart.
• Choose the Right Chart: Match the chart type to the question you're asking. Use line charts for trends, bar charts for comparisons, and scatter plots for relationships.
• Use Color with Intent: Color should guide attention and enhance meaning, not just add decoration. Use bright, saturated colors for emphasis and muted colors for context.
• Label Clearly: Make sure your charts have titles, axes are labeled, and units are clear. Someone should be able to understand your viz without needing you to explain it.

Final Thoughts

Simply put, a "viz" is any visual chart or graph you create in Tableau to analyze and communicate data. Mastering the art of building clear, effective vizzes is the core skill that allows you to move beyond spreadsheets and uncover the stories hidden in your data.

While a powerful tool like Tableau offers incredible depth for data analysts, we know that the initial setup and learning curve can be a hurdle, especially for business owners and marketers who need answers quickly. That’s why we created Graphed. Our platform allows you to connect all your data sources and create real-time dashboards just by asking questions in plain English - no dragging, dropping, or chart-building required. It turns hours of analysis into a simple conversation to help you get insights in seconds.