Intro to Visualizations

Visualizations are graphical data elements that add visual context to your analysis. They allow you to create, explore, and view your data in a more focused and digestible format.

By adding visualizations to a workbook, you can reveal patterns, trends, outliers, and correlations crucial to creating a compelling data narrative. Build each visualization to deliver specific data insights and answer important questions that help you make better business decisions.


Summary of Content

Types of Visualizations

Bar Chart

Line Chart

Area Chart

Scatter Plot

Combo Chart

Box Chart

Donut/Pie Chart

Sankey Diagram

Funnel Chart

Gauge Chart

Region Map

Point Map

GeoJSON Map

Custom Configurations

Properties

Formatting

Related Resources


Types of Visualizations

Effective visualizations are essential to telling meaningful data stories, but choosing the right types of visualizations can be a challenge. Consider the type of data you want to visualize, the questions you need to answer, and the users who will view and consume your analysis.

The following information can help you choose visualizations best suited for a clear and detailed narrative.

Bar Chart

Show how values vary across categories or groups of data. Compare values against each other, in relation to a reference mark, or as proportions of a whole.

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Line Chart

Show how values of one or more metrics change over time. Spot trends and identify anomalies in your dataset.

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Area Chart

Illustrate the magnitude or cumulative values of one or more metrics over time. Compare categories or groups of data, or evaluate the data composition or part-to-whole relationship.

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Scatter Plot

Demonstrate the presence and strength of a correlation between metrics. Analyze patterns, understand distribution, and identify outliers in your dataset.

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Combo Chart

Combine bar, line, area, and/or point marks to compare multiple types of metrics. Evaluate the relationship to identify correlations and variations between the datasets.

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Box Chart

Show the value distribution of one or more metrics. Mark the minimum, median, and maximum values, and identify outliers in your dataset.

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Donut/Pie Chart

Portray values as proportions of a whole to convey the data distribution and part-to-whole relationship.

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Sankey Diagram

Show how data flows and changes throughout a process or system. Compare the movements and proportions of data across different paths to analyze distributions, workflow, networks, etc.

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Single Value

Display a single-value metric. Measure it against another value and show relative performance as a percentage, delta, or absolute value comparison.

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Funnel Chart

Measure values across sequential stages in a linear process. Gain insight into inputs across stages, identify bottlenecks and other issues, and assess the overall health of the process.

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Gauge Chart

Measure a single-value metric against a radial scale. Evaluate growth, assess performance, and track progress toward a goal.

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Region Map

Illustrate the scale of data distribution by country, state, county, city, etc. Compare data proportions or magnitudes across regions.

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Point Map

Illustrate the geographic distribution of data with precise positioning based on latitude and longitude. Reveal spatial patterns and identify outliers in your dataset.

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GeoJSON Map

Convert geographic features from geospatial data and illustrate the data distribution across custom-mapped regions.

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Custom Configurations

Visualizations feature various properties and formatting options that impact how your data is represented. With a wide range of customizable configurations, you can enhance your visualizations and ensure they present meaningful and actionable information.

Properties

The Element properties panel requires you to select a visualization type and configure source columns to define chart properties (axes, colors, tooltips, etc.).

You can convert data value types, change the data aggregation or truncation, and customize chart markers and tooltips. Depending on the visualization type selected, you may also have options to change the chart orientation, modify data stacking, and add trellis rows and columns.

Element properties panel in Edit mode

Element properties panel in Explore mode

Formatting

The Element format panel allows you to customize the appearance of various components, including the visualization title’s content, size, and alignment. Depending on the visualization type selected, you may also be able to format the background, axes, legend, data labels, reference marks, trend lines, etc.

Element format panel in Edit mode

Element format panel in Explore mode


Related Resources