Time is a Challenge!
Creating time-aware SQL scripts can be challenging, depending on the level of complexity and the specific requirements of the task.
If you’re only dealing with basic requirements, like extracting data based on date ranges or filtering records based on time stamps, then it can be relatively easy. You just need to know how to use the right date/time functions and conditional statements in SQL.
But watch out for tricky tasks that require handling time zones, leap years, and daylight savings. But there’s more! AI-ready data requires complex feature engineering with calculations like entropy, clumpiness, and more – all while allowing for the occurrence timestamp of events, validity periods for attributes, creation timestamps, multiple time windows, table joins, layered aggregations, spaghetti code, resources optimization, and more.
When you think about it, creating time-aware SQL scripts can be a nightmare. And maintaining them over time is even worse. No wonder data scientists and data engineers are in high demand, and so many AI projects take too long to complete, yet fail to deliver results!
It must be possible to efficiently and elegantly code features that are time-aware. What is the most elegant and efficient time-aware feature you have engineered using SQL?