Which option best describes the sequence to retrieve and append historical data to a current dataset?

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Bringing historical data into a current dataset is about two steps: retrieving the data from its source and then adding those records to the existing dataset. Extracting grabs the historical records from their storage location, and appending places those records at the end of your current dataset, preserving the fields and structure you already have. This approach is ideal when you want to grow the dataset with past data without altering or reshaping existing rows or creating new relational links.

Joining would merge datasets based on related keys, which isn’t the same as simply adding new rows. Parsing and normalization focus on interpreting and standardizing values rather than fetching data. Filtering and sampling reduce or select parts of the data rather than retrieving new historical records to add.