The analytics team must deliver a Power BI report to senior executives that preserves the exact figures captured at the close of the fiscal month. After the report is published, new transactions will continue to flow into the production database each day, but the board presentation must always display the original month-end numbers and remain unchanged for auditing purposes. Which data versioning technique should the team apply to the dataset that feeds the report?
Enable incremental refresh so the dataset automatically appends new transactions.
Capture a month-end snapshot and publish that static dataset.
Connect the report directly to the live real-time data feed.
Apply row-level security to restrict users to month-end records only.
A point-in-time snapshot freezes the data as it existed when the fiscal month closed, producing an immutable version that can be queried repeatedly without being altered by later transactions. Real-time connections would keep the numbers changing, incremental refresh would still pull in new rows on every scheduled update, and row-level security only limits who can see specific rows but does not stop the underlying data from updating. Therefore, publishing a snapshot of the month-end dataset is the most appropriate technique when auditability and consistency over time are required.
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