Working in data science and analytics for seven years, I actually have created and queried many tables. There are many times I’m wondering, “What does this column mean?” “Why are there two columns with the identical name in table A and table B? Which one should I exploit?” “What’s the granularity of this table?” etc.
If you happen to’ve faced the identical frustration, this text is for you!
In this text, I’ll share five principles that can show you how to create tables that your colleagues will appreciate. Please note that that is written from the attitude of an information scientist. Subsequently, it’ll not cover the standard database design best practices but concentrate on the strategies to make user-friendly tables.
Maintaining a single source of truth for every key data point or metric could be very vital for reporting and evaluation. There shouldn’t be any repeated logic in multiple tables.
For convenience, sometimes we compute the identical metric in multiple tables. for instance, the Gross Merchandise Value (GMV) calculation might exist in the client table, monthly financial report table, merchant table…
