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Worrying over Columns or Rows

John Mount explains an attitude difference:

I say: if you are a data scientist or working on an analytics projectworry over columns not rows.

In analytics “rows” are instances, and “columns” are possible measurements. For example: each click on a website might generate a row recording the visit, and this row would be populated with columns describing what was clicked on (and if you are lucky there are more records recording what else was presented and not clicked on).

Read the whole thing. This is also why formats like Parquet and ORC are so popular for data analysis. Same goes for business intelligence people, who reason mostly over columns, leading to columnstore indexes being so useful.

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