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.