DAA-C01 Question 266
Single answerCustomize data presentations using filtering and editing techniquesA data analyst is building a Snowsight dashboard for regional sales managers. The managers want to review only their own region's records, quickly exclude cancelled orders from visualizations, and rename several column headers in a worksheet result so the business users see friendly labels such as "Net Revenue" instead of underlying field names. The analyst wants to do this without changing the underlying table definitions because other teams rely on the existing schema. Which approach best meets these requirements?
- A
Apply worksheet and dashboard filters in Snowsight to limit the displayed data, and use SQL column aliases in the query to present business-friendly column names.
- B
Rename the physical columns in the base tables so Snowsight automatically shows the new labels everywhere, and use a WHERE clause only after publishing the dashboard.
- C
Create a new warehouse for each region and assign managers to region-specific warehouses so each dashboard automatically shows only relevant rows.
- D
Clone the source tables for each region, delete cancelled orders from each clone, and point the dashboard to the cloned tables with renamed columns.
Show answer and explanation
Correct answer: A
Explanation
The best solution is to customize presentation at the query and dashboard layer rather than modifying shared source objects. In Snowflake, SQL aliases are a standard way to rename columns in query results for clearer presentation, which is especially useful in worksheets and dashboard tiles. Snowsight also provides filtering capabilities so analysts can narrow displayed data for exploration and dashboard consumption without altering the underlying tables. This aligns with best practices: keep source schemas stable for shared use, apply filters to control what users see, and use query formatting or aliases to improve readability. By contrast, warehouses do not enforce row filtering, and cloning or renaming base tables introduces unnecessary risk and maintenance.
- A. Correct.
Correct. Snowsight supports filtering displayed results and dashboard content so users can focus on relevant subsets of data, such as a region or excluding cancelled orders. Using SQL aliases like SELECT revenue AS "Net Revenue" allows the analyst to edit the presentation of result-set column names without changing the underlying schema. This satisfies the requirement to customize presentation while preserving shared table definitions.
- B. Incorrect.
Incorrect. Renaming physical columns in base tables changes the shared schema and can break downstream dependencies for other teams, which directly violates the requirement. Also, filtering should be part of the query or dashboard design before delivery, not something deferred until after publishing as the primary strategy.
- C. Incorrect.
Incorrect. Warehouses control compute resources, not row-level presentation or filtering. Assigning managers to different warehouses does not automatically restrict the rows they see in Snowsight dashboards. This option confuses compute isolation with data filtering and presentation logic.
- D. Incorrect.
Incorrect. Cloning tables per region and deleting cancelled orders is operationally heavy, introduces data duplication, and changes the dataset rather than just customizing how it is presented. It also creates unnecessary maintenance overhead when the requirement can be handled with filters and query-level aliases.