A dashboard developer notices that Age is available in the sourced data module. A request has been made to 'bucket' those age values into 5 groups, Ages 0-6, 7-12, 13-21, 22-55, and 55 and over. How…

Question

Options

• Aset range values in the data module
• Buse the Create new table feature
• Cselect the Age column, and select Create data group
• Ddefine a Case..When calculated attribute in the dashboard

• A
  83% (38)
• B
  2% (1)
• C
  7% (3)
• D
  9% (4)

Explanation

Setting range values in the data module is the correct approach because it allows you to define numeric boundary conditions (0–6, 7–12, 13–21, etc.) directly within the data source layer, making those age buckets reusable across any dashboard or report that consumes that module - keeping business logic centralized and consistent.

Why the distractors are wrong:

• B (Create new table) creates an entirely new data structure, which is far more than needed for simple grouping and doesn't address bucketing logic.
• C (Create data group) is used for grouping discrete/categorical values (like product names or regions), not for defining numeric ranges on a continuous field like Age.
• D (Case..When calculated attribute in the dashboard) could technically produce the same result, but it defines the logic at the dashboard level - meaning it wouldn't be reusable in other dashboards and violates the requirement to define it in the source data module.

Memory tip: Think "ranges belong at the source." Whenever a question involves bucketing continuous numeric data (age, salary, score) and specifies the source/data module layer, look for the option that sets range values - not groups (categorical), not tables (structure), not dashboard-level expressions (wrong layer).

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