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Data Attributes

Data attribute actions allow you to refine how a data attribute behaves after it has been added to a dashboard or bound to a visualization. These actions do not alter the underlying dataset. Instead, they offer a set of tools that help you control formatting, structure, aggregation, and interpretive behavior so the visualization presents information clearly and accurately. By adjusting these settings, you can standardize numeric displays, apply transformations to support analysis, or enhance category and hierarchy relationships. This overview introduces the primary actions available for data attributes and links to articles that describe each action in detail.

Available Actions

The following actions are available for refining how data attributes behave within dashboards and visualizations:

  • Data Attribute Actions – Provides a high-level overview of the actions available from the data attribute menu, including changing the aggregation method, applying quick functions, setting attribute-level filters, renaming an attribute, removing it from the visualization, or locating it within the data source panel.

  • Rename a Data Attribute – Update the display name to make the attribute more descriptive or meaningful in context.

  • Bind a Date to a Dashboard Scenario – Connect a date attribute to a scenario timeline so the dashboard can interpret and use it for time-based operations.

  • Modify Data Format – Adjust numeric, date, and text formatting to control how values appear.

  • Modify Display Unit – Change the scaling applied to numeric values, such as none, thousands, or millions.

  • Change Aggregation Method – Choose how the attribute should be summarized, including sum, average, count, min, or max.

  • Apply Quick Functions – Apply predefined calculations such as period-over-period comparisons, running totals, and percentage changes.

  • Filter Data Attributes – Use attribute-level filtering to limit the values that appear in the visualization.

  • Create a Hierarchy Field – Build a drillable multi-level hierarchy from related categorical attributes.

  • Measures and Calculated Columns – Create new logic-based values or expressions that are not present in the underlying dataset.

  • Change Timezone Format – Adjust the timezone settings for time-based attributes to match the dashboard’s requirements.

  • Modify Geographic Data – Standardize or correct geographic attributes so they align with mapping requirements.