Data Modelling Simplified #shorts

本站添加: 2026-05-06

[00:00:00]In data warehouse modeling design interview questions, a lot of people feel confused about various basic fundamentals of a star schema, a snowflake schema, and galaxy schema. So, let me simplify it for you with a simple explanation. So, save, share, and follow to learn effectively. Also, to explain it in much more detailed way with practical example, I have created a very detailed PDF. So, comment to DWH and I will send that PDF in your DM. So, in a star schema, basically, there is going to be one fact table only and that will be connected to various dimension tables which you can see here. There won't be more than one fact table, so that is your a star schema. Snowflake schema is the extended version of the star schema itself where you will be having one fact table and there will be several connected dimension tables. And these dimension tables are now breaking down into the normalized form. In the star schema, they were in the denormalized form. Here, you can see the customer dimension table is breaking down into the transaction and location. Similarly, the store is breaking down into the region as well and the product is breaking down into two more dimension tables, the manufacturer and the category. So, this is the extended version of the star schema. In the galaxy schema, the concept is simple.

[00:01:15]There can be more than one fact table which will be connected with various common dimension table which you can see here like this fact table, this fact table connected with both of them. So, this is the basic difference between the star schema, snowflake schema, and galaxy schema. And if you are failing in your data warehouse modeling design interview rounds and not able to create the production grade of data warehouse models, then do check out my platform GrowDataSkills. I have created a detailed program with the practical industrial case studies, so that will be pretty helpful.