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    Question

    Which of the following best describes a method to handle

    inconsistent data when integrating datasets from different sources?
    A Retaining original values from each source without modification Correct Answer Incorrect Answer
    B Ignoring discrepancies to preserve data integrity Correct Answer Incorrect Answer
    C Standardizing formats, such as date and time, across datasets Correct Answer Incorrect Answer
    D Converting all data to numerical format Correct Answer Incorrect Answer
    E Using random values to fill inconsistent entries Correct Answer Incorrect Answer

    Solution

    Standardizing data formats is crucial when merging data from multiple sources to ensure uniformity. Date and time formats, for example, may differ across datasets (e.g., DD-MM-YYYY vs. MM-DD-YYYY). Without standardization, analyzing or comparing these fields becomes problematic, as discrepancies will lead to inaccuracies. Standardizing data formats allows datasets to be integrated seamlessly, supporting accurate analysis and decision-making. Option A is incorrect because keeping original values without standardization leads to inconsistencies, complicating analysis. Option B is incorrect because ignoring discrepancies allows inconsistencies to persist, harming data quality. Option D is incorrect as converting all data to numerical form may distort categorical or textual information, reducing data interpretability. Option E is incorrect because using random values introduces arbitrary changes, reducing data reliability.

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