Analytics has become a man power intensive activity.Man power is very expensive on top of it Analytics field is replete with jargon, as a result it has going beyond the reach of smaller companies. With today’s advances in technology there is no reason why a large part analytics can be automated. So taking cue from “lean manufacturing” and “lean startup” we should also aim towards “lean analytics”.
A large part of lean analytics would involve automating various steps, reducing wastage of analysis and data, and building compute-efficient models. It all starts at data gathering stage. Once the data is machine readable most of the other analytics can be automated.
There are ready tools for data munging, ETL etc. Statistical analysis can be completely automated. Even model building and prediction can be largely automated. So data gathering is the key for making analytics lean. So here are the hygiene factors for lean data collection:
- Reduce human error as much as possible through data collection automation (for ex. have drop boxes in forms instead of text)
- Try to figure out data model in advance but keep scope for unstructured data
- Dont collect all the data you can get. You have something doesn’t mean you need it
- Set a process for cleaning before storing
Follow
