What is One Big Table? Exploring When to Use it, When Not to Use it and My Personal Experience
Unlocking Data Potential: Simplify and Supercharge Analytics with One Big Table design
In my data engineering feed on LinkedIn, Medium, Reddit etc., I started noticing a lot of attention being given to designing tables as One big table (OBT).
If you haven’t heard about it before, it isn’t inherently a new concept/idea in data engineering. It has been used in data modeling for many years, particularly in scenarios where simplicity and performance are prioritized. However, it seems a lot of data engineering team across organizations are adopting this approach.
What is One Big Table?
OBT is a modelling technique where all the data attributes needed for analytics are stored into one, wide, denormalized table. Unlike the traditional data models such star schema, snowflake schema, OBT eliminates the need to join data between dimension and fact tables. This means all the columns your Power BI/Tableau/data analyst/data science team would need are available in one table as opposed to being split between dimension and fact tables.
