Re:The Rise of SQL-Based Data Modeling
by atwebb on Thursday January 30, 2020 @10:52AM
(#22192221)
> denormalization, while useful for many things, isn't always your best option.
From my view, it is generally not a good option for cases it wasn't designed for, an example being non-analytical reporting. If you are running operational support, getting the source data immediately and aggregating/displaying can be more helpful than modeling for analytics workloads. The line between these is blurred in most orgs. To the OPs point, data modeling seems like a sidenote in most analytical discussions. You can accomplish a lot using the star model which is essentially:
Prepare things to be fast by sorting them into proper groups (fact/dim/bridge)
Rely on ints
Store atomic data
Provide summaries/aggregates
Model after the questions you ask; not the system it comes from
From my view, it is generally not a good option for cases it wasn't designed for, an example being non-analytical reporting. If you are running operational support, getting the source data immediately and aggregating/displaying can be more helpful than modeling for analytics workloads. The line between these is blurred in most orgs. To the OPs point, data modeling seems like a sidenote in most analytical discussions. You can accomplish a lot using the star model which is essentially:
Prepare things to be fast by sorting them into proper groups (fact/dim/bridge)
Rely on ints
Store atomic data
Provide summaries/aggregates
Model after the questions you ask; not the system it comes from