👱🏻♀️🎀 DATA MODELS ARE LIKE BARBIES 🛼🕺
📖 Background
If you are working towards a career as a Data Engineer a DataCamp certification is a great way to show you are developing the data management skills you will need. You will be able to demonstrate to employers that you have built the SQL skills that will be the foundation to your future career.
🎓 Step 1: Get Certified!
📝 Step 2: Explain your choice of metrics
Now the project is over, you are reviewing how the project went with some of your colleagues. One of your colleagues is discussing the data model that you are using and in particular the star schema. After the meeting the intern on the team sends you a message and asks what a star schema is.
In no more than 200 words, explain the different data models that you can use to the intern.
There are two types of data models: star and snowflake schema. A star schema is like a Barbie. In Barbie’s world, you have the doll in the center and its accessories that can be attached to it, such as clothes, cars, and houses. Similarly, a star schema has a central table, known as a fact table, with all quantitative data. A fact table for Barbies could hold data like the number of sales or the average price for each Barbie model. Just as Barbie’s accessories characterize her, in a star schema, there are other tables connected to the fact table that hold qualitative information—these are called dimension tables. In a Barbie-themed star schema, dimension tables could specify which cars or clothes Barbie dolls can have.
A snowflake schema evolves from the star schema by further organizing these accessories. It's like breaking down Barbie's clothes into categories, such as types or colors. In data terms, snowflake schema splits a dimension table into more detailed tables and this process is called normalization, which improves data integrity but also adds complexity to database management.