There's value in both types of analyses. For knowing what users do after they perform action "A", "B" & "C", many people currently rely on implementing Map/Reduce programs.
That can be a bit heavyweight if you want to simply compare people who did action "A" or "B", filter based on complex criteria, or apply simple analytic functions. Also, apart from standard relational algebra operators, SQL provides a lot of convenience functions for math operations, string manipulations, date and time formatting, pattern matching, and so forth. These may come in handy to users who want to quickly gather insights out of their data.
You're right, there is value from SQL over event data, however, I feel like it's a missed opportunity to simply apply the same paradigms to a different type of data. I'm not suggesting that SQL be thrown out but a new language needs to be available specifically for event data.
Comments
There's value in both types of analyses. For knowing what users do after they perform action "A", "B" & "C", many people currently rely on implementing Map/Reduce programs.
That can be a bit heavyweight if you want to simply compare people who did action "A" or "B", filter based on complex criteria, or apply simple analytic functions. Also, apart from standard relational algebra operators, SQL provides a lot of convenience functions for math operations, string manipulations, date and time formatting, pattern matching, and so forth. These may come in handy to users who want to quickly gather insights out of their data.
You're right, there is value from SQL over event data, however, I feel like it's a missed opportunity to simply apply the same paradigms to a different type of data. I'm not suggesting that SQL be thrown out but a new language needs to be available specifically for event data.