DAA-C01 Question 244
Single answerCreate and manage custom filtersA data analyst is building a Snowsight dashboard for regional sales managers. The dashboard contains several charts based on the same SALES table, and managers want one reusable filter that lets them view only the data for their selected sales region across all tiles on the dashboard. The analyst also wants the filter logic to be easy to maintain if the list of allowed regions changes later. Which approach best meets these requirements?
- A
Create a dashboard-level custom filter based on the REGION column and apply it to the relevant tiles.
- B
Add a separate WHERE REGION = '
' clause to each chart query and update each tile individually when a region changes. - C
Create a calculated field in each chart that hard-codes the region list, then use that field as a local visualization filter.
- D
Duplicate the dashboard once for each region so each manager opens a different pre-filtered dashboard.
Show answer and explanation
Correct answer: A
Explanation
In Snowsight, custom filters are used to create reusable, interactive filtering controls for dashboard consumers. When multiple visualizations need to be filtered consistently by the same business attribute, the best practice is to create a dashboard-level filter rather than embedding filter logic separately in each query or duplicating content. This improves maintainability, consistency, and user experience. Using the underlying REGION column as the filter source also keeps the implementation aligned with the actual data model, making future updates easier if valid values change. This matches standard dashboard design guidance in Snowflake Snowsight, where centralized filters are preferred for cross-tile filtering and simplified management.
- A. Correct.
Correct. A dashboard-level custom filter is designed for exactly this use case: one reusable filter control that can affect multiple tiles built from compatible data sources. Using the REGION column as the basis for the custom filter centralizes maintenance and gives managers an interactive way to change the region without editing every chart.
- B. Incorrect.
Incorrect. While this would technically restrict each chart, it does not create a reusable managed filter. It also creates a maintenance problem because every tile query must be edited separately if filter behavior changes. This approach does not scale and is not aligned with dashboard filter best practices.
- C. Incorrect.
Incorrect. Hard-coding region logic inside separate calculated fields on each chart duplicates logic and makes changes harder to manage. It also limits reuse and increases the risk of inconsistent filtering across tiles. Custom filters are intended to provide centralized, interactive filtering rather than repeated per-chart logic.
- D. Incorrect.
Incorrect. Duplicating dashboards for each region is operationally inefficient and difficult to maintain. It increases content sprawl, introduces versioning issues, and removes the flexibility of letting users dynamically change the filter within a single dashboard.