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Practical Guide: Google Data Studio (A-Z) Charts

Google Data Studio Charts explained with an example and use case scenario

Google Data Studio Chart Guide

Scorecard in Data Studio

Scorecard in Data Studio

1. Scorecard

Scorecards display a summary of a single metric and are the most commonly used way to visualize core key performance indicators (KPIs).

Pie/Doughnut chart in Data Studio

Pie/Doughnut chart in Data Studio

2. Pie/Doughnut chart

A Pie/Doughnut chart expresses a part-to-whole relationship in a data set. It will always add up to 100%. So, if, for instance, you want to show "How does 100% divide up into multiple shares?" you should always use a Pie/Doughnut Chart with % as a data label.

Bullet Chart in Data Studio

Bullet Chart in Data Studio

3. Bullet chart

Bullet charts display a single metric performance and progress towards a certain goal or against a benchmark. You can optionally display a target value, and set it up to 3 ranges.

Gauge Charts in Data Studio

Gauge Charts in Data Studio

4. Gauge chart

Gauge charts display a single metric performance and progress towards a certain goal or against a benchmark.

Line Charts/Time Series Charts in Data Studio

Time Series Charts in Data Studio

5. Line chart/Time series chart

Line charts are best for tracking changes over short or long overtime. Compare how several things change over time relative to each other. When minor changes exist, line graphs are better than bar graphs. So If you hear that key phrase "over time," that’s your clue to consider using line charts for your data.

Column Charts in Data Studio

Column Charts in Data Studio

6. Column chart

A Column chart shows comparisons among discrete categories. One axis of the chart shows the specific categories being compared, and the other axis represents a measured value. The bars can be plotted vertically or horizontally.

Combo Charts in Data Studio

Combo Charts in Data Studio

7. Combo charts

Combo charts use both axes to show a comparison between different KPIs. They work in a similar way to Column charts except with the option to configure how to display individual metrics (Line and Pub/Bar). The right axis is often used If a data set is significantly smaller than the rest of the KPIs.

Table in Data Studio

Table in Data Studio

8. Table

Tables represent quantitative information where precise values can be required in some cases. However, this is not exclusive in this information age. My personal favorite method of using tables treats them as a raw data export into Microsoft Excel and Google Sheets for detailed analysis.

Pivot Tables in Data Studio

Pivot Tables in Data Studio

9. Pivot Table

A Pivot Table stores the summary of a specific data set in a condensed manner or groups data together in a meaningful way. My personal favorite is to treat Pivot Tables as raw data export tables into Excel and Google Sheets for detailed analysis.

Area Charts in Data Studio

Area Charts in Data Studio

10. Area chart

An Area Chart is best used to show the distribution of categories as parts of a whole changing over an interval. As the area inside the chart is plotted to convey whole numbers, an Area Chart does not work for negative values.

Scatter Charts in Data Studio

Scatter Charts in Data Studio

11. Scatter chart

A scatter chart will show the relationship between two different variables represented by the X and Y axes.

Bubble Chart in Data Studio

Bubble Chart in Data Studio

12. Bubble chart

Bubble Chart = Scatter Chart + Bubble Size

A Bubble chart shows the relationship between two different variables represented by the X and Y axes, with Bubble Size (optional) representing the optional metric.

Geo Maps Charts in Data Studio

Geo Maps Charts in Data Studio

13. Geo map chart

Geo charts are an easy way to visualize data in maps to compare how a measurement varies across a geographic area. The dimensions are related to continents, countries, regions/states and cities, with your desired metrics as a data point.

Treemap in Data Studio

Treemap in Data Studio

14. Treemaps

Treemaps show parts of a whole and display hierarchical information.

Configuration across charts in Google Data Studio

Background and Border in Google Data Studio

1. Background and Border in Google Data Studio

Background and Border offer ways to customize the appearance of charts individually or on the report level. For instance, you may want to customize your charts to match your company branding color. Consistent and meaningful use of color makes your reports more attractive and easier to understand. You can apply color and border options to every available chart in Google Data Studio. If you are unsure about a uniform design, please use the standard design available in Google Data Studio. The color and style settings of these designs are set so that the reports are visually appealing and suitable for color-blind users.

Missing Data in Google Data Studio

2. Missing Data in Google Data Studio

This option controls how to display missing values according to your preference. For example, when data is missing from the scorecard, you can choose to show blanks (""), 0 (Zero), hyphens (-), the words "null" or "No data."

Conditional Formatting in Google Data Studio

3. Conditional Formatting in Google Data Studio

Based on the data, you can set the font and background colors used in your charts. For example, if Revenue is greater than 100000, then set the scorecard text color to green.

Chart Header in Google Data Studio

4. Chart Header in Google Data Studio

Chart headers allow viewers to perform several actions on charts, such as data export, drilling up or down, and view charts in explorer tools. Available across charts in Google Data Studio and the color is also customizable.

Legends in Google Data Studio

5. Legends in Google Data Studio

These options decide the placement and visibility of the chart legend. Legend Alignment and Max lines are also configurable.

Reference Lines and Trendlines in Google Data Studio

6. Reference Lines and Trendlines in Google Data Studio

Reference lines show how the data in a chart compares to a reference value or let you show target values and set thresholds and benchmarks. For example, you can use reference lines to visualize daily sales against a target sales figure.

Trend lines reveal the general tendency of the data on a chart. Trend lines allow you to spot patterns and make predictions from otherwise random data. You can add trend lines to time series and scatter charts.

Enjoy reading the guide? I have explained every chart available in the new Data Studio Book here. Visual explanations for graphs configurations, style, format, and recommendations. So you can also see how the final result will look and why one design is better than others for the same chart.

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