When dealing with multiple date columns from different data sources, it's crucial to ensure consistency and accuracy in the dataset. The best practice is to merge the date columns and standardize the date format across the entire dataset. This approach helps maintain data integrity, simplifies analysis, and avoids confusion that could arise from having multiple date formats. Unifying the date format is particularly important when the data will be used for time series analysis or when dates are key to joining with other datasets.
References:
* Best practices in data merging emphasize the importance of a single point of reference and the need to avoid data loss or damage to individual data structures1.
* Power BI guides suggest that merging columns should be done carefully to maintain data integrity and avoid errors and inconsistencies2.
* Oracle Blogs highlight the need for a consistent number of columns among data sources when combining data with unions3.
* Excel tutorials recommend organizing data before merging and using formulas for complex merges4.
* An Excel guide on merging date and time columns advises employing functions to ensure seamless handling of non-date values5.