A transportation company maintains a master table containing shipment details. Each day, a second dataset of newly shipped orders is collected with matching columns. Which method prevents overwriting previous entries and includes the new rows at the bottom of the master table?
Transform both tables into a pivoted view and combine them based on shared dimensions
Conduct a Data Purge Update (DPU) on existing entries in the master table and import the new dataset in its place
Rename the columns in the original table, then copy rows one by one into the new table
Ensure both tables share column names, then insert the new rows beneath the existing data in the master table
One method inserts the new rows from the secondary dataset into the master table, preserving existing records. Overwriting or merging replaces past entries, and pivoting or renaming columns alone does not add new records properly. The recommended process ensures the master table retains its original entries while growing with the latest shipments. A Data Purge Update (DPU) is not a real term.
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What are the main reasons for not overwriting previous entries in a master table?
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How do you ensure both tables have matching column names before the insertion process?
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What are some common tools or methods used to insert new rows into a master table?