DA0-001 · Question #251
Company A recently merged with Company B and will be reporting first quarter numbers soon. Prior to the release, an analyst wants to ensure the data was accurately blended together. Which of the follo
The correct answer is D. Review the files separately and ensure the blended totals match.. To efficiently verify the accuracy of merged datasets, reviewing the original files separately and confirming that their aggregated totals correctly sum up to the blended total is the most effective approach. This method provides a high-level validation of data integration withou
Question
Company A recently merged with Company B and will be reporting first quarter numbers soon. Prior to the release, an analyst wants to ensure the data was accurately blended together. Which of the following is the MOST efficient way to ensure the data is reported correctly?
Options
- AAssume the data was blended together and wait for feedback.
- BFilter on every column to look for inconsistencies in the data.
- CSpot check a few numbers to look for inconsistencies.
- DReview the files separately and ensure the blended totals match.
How the community answered
(53 responses)- A11% (6)
- B6% (3)
- C4% (2)
- D79% (42)
Why each option
To efficiently verify the accuracy of merged datasets, reviewing the original files separately and confirming that their aggregated totals correctly sum up to the blended total is the most effective approach. This method provides a high-level validation of data integration without needing to inspect every detail.
Assuming data accuracy without verification is highly risky and unprofessional, potentially leading to incorrect reporting.
Filtering on every column to look for inconsistencies would be an extremely time-consuming and inefficient process for a large dataset, making it impractical for initial verification.
Spot checking a few numbers might catch some inconsistencies, but it's not thorough enough to ensure the overall integrity and accuracy of a large blended dataset.
Reviewing the files separately and ensuring the blended totals match is the most efficient and robust way to verify data accuracy after a merge. This approach provides a high-level validation, confirming that no data was lost or duplicated during the blending process, and helps catch systemic errors.
Concept tested: Data quality assurance - data blending verification
Source: https://learn.microsoft.com/en-us/power-bi/connect-data/desktop-tutorial-combine-data-with-power-bi-desktop
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