CompTIA Data+ DA0-002 (V2) Practice Question

After last night's refresh, the ecommerce dashboard is showing every order three times, so the total revenue KPI has tripled. The visualization uses a live connection to the company's Snowflake data warehouse, and the ETL job's execution log reported no errors. No changes were published to the dashboard itself. Which action should the data analyst take first to determine whether the duplication originates in the visualization layer or in the warehouse?

Increase the BI server's memory allocation to handle larger result sets.
Run a SQL query on the warehouse table to count rows per unique order ID and check for duplicates.
Clear the dashboard's cache and republish the workbook.
Post a question to the BI vendor's community forum to ask about duplicate-row rendering defects.

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Answer Description

Duplicated records can be introduced either in upstream tables (for example through an ETL load or an unexpected one-to-many join) or by the visualization layer's rendering logic. The quickest way to isolate the source is to validate the data at its source: run a direct SQL query against the fact table and count the rows (or distinct order IDs). If duplicates exist in the table, the problem is upstream; if the counts are correct in SQL but wrong in the dashboard, the issue is in the BI tool configuration. Clearing caches, tuning server memory, or opening a vendor ticket may be necessary later, but none of those steps establishes where the bad data appears, so they are not the appropriate first move.

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