An analyst has a collection of daily shipment records from multiple distribution centers. They aim to generate a concise table that shows total shipments per center each month. Which approach achieves this goal while reducing the volume of data?
Use recoding to give each center a unified identifier
Reformat the date fields into a shorter string format for grouping by day
Group daily entries by center and month, then sum shipment totals
Merge daily data from each source into a single table to consolidate all rows
Summarizing shipments by center and month reduces many rows into monthly totals. Merging daily records creates a single dataset but does not summarize data. Recoding IDs alters identifiers and does not create monthly totals. Reformatting dates changes the display without combining daily entries.
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Why is grouping data by center and month an effective approach for summarizing shipment records?
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What is the primary difference between merging data and grouping data in this context?
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What does 'reformatting date fields' mean, and why doesn’t it achieve monthly totals in this case?