What's the difference between joining and blending?

In data analysis, "joining" combines data from multiple sources by directly merging their rows based on a shared field, while "blending" combines data from different sources by aggregating each source separately before bringing them together, allowing for data from different levels of granularity to be combined without creating unnecessary redundancy; essentially, joining combines data at the raw level, while blending combines data after aggregation.

Key points to remember:
Data combination:
Joining merges data directly at the row level, creating a single combined table, while blending aggregates data from each source before combining them.

Granularity:
Blending is useful when data sources have different levels of detail, as it allows you to combine aggregated data from each source.

When to use:
Use joining when you need to combine detailed data from different sources with the same level of granularity, while blending is ideal when you need to combine data from different sources with varying levels of detail.

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