Which of the following is an objective of verification?

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Multiple Choice

Which of the following is an objective of verification?

Verifying data is about making sure the data you end up with actually serves the original goal of the analysis or decision. It asks: does the collected and cleaned dataset align with what you set out to accomplish, including covering the right scope and staying true to the needed context so the results will be meaningful for the purpose? This perspective matters because you can clean and standardize data, or handle missing values, or even encrypt it, yet still end up with a dataset that doesn’t address the intended question or decision. Verifying ensures the data collection and cleaning steps produced a dataset fit for its use. For example, if the goal is to evaluate customer satisfaction over a particular quarter, verification checks that the data include responses from that quarter, the right satisfaction metrics, and no changes in how questions were asked that would bias the results. The other activities—imputing missing values, standardizing formats, or encrypting data—are important, but they don’t by themselves confirm that the data will address the original purpose.

Verifying data is about making sure the data you end up with actually serves the original goal of the analysis or decision. It asks: does the collected and cleaned dataset align with what you set out to accomplish, including covering the right scope and staying true to the needed context so the results will be meaningful for the purpose?

This perspective matters because you can clean and standardize data, or handle missing values, or even encrypt it, yet still end up with a dataset that doesn’t address the intended question or decision. Verifying ensures the data collection and cleaning steps produced a dataset fit for its use.

For example, if the goal is to evaluate customer satisfaction over a particular quarter, verification checks that the data include responses from that quarter, the right satisfaction metrics, and no changes in how questions were asked that would bias the results. The other activities—imputing missing values, standardizing formats, or encrypting data—are important, but they don’t by themselves confirm that the data will address the original purpose.

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