Operational vs Analytical Systems
Operational systems are where data is born — services reading and updating data as users act. Analytical systems hold a read-only copy restructured for heavy analysis. The book's most-used divide.
What is it?
Three user groups want different things from the same data: backend engineers (build/serve), business analysts (BI reports), data scientists (insights, ML features). Operational systems serve users' actions; analytical systems serve people examining data that was already generated — read-only, restructured for heavy processing. From this split grew two roles: data engineers (connect the two worlds, own infrastructure) and analytics engineers (model data for analysis).
What I learned
Data spends it’s life crossing this divide — so I need to understand both sides, even if I work on one. Misreading which side a system belongs to is how people end up running analytics on production OLTP databases.
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