In this recipe, we will learn and explain in depth how to merge data as well as about the dimension merging capabilities and behavior. Creating several queries from the same universe can help us resolve many data issues that can't be answered by using a single query:
If the queries contain contradicting sets of conditions that require separation.
Different time frames.
Requirement to perform the union of two sets of data without the limitations of combined queries.
Using different granularity data that can't be combined in a single query (monthly aggregative data and daily data).
Using the outer join logic—depending on the database, the data warehouse design, and the universe structure, for some business questions, we require to display unmatches between certain data values. A good example for this kind of business question would be, "In which months were certain products not sold?".