Whsat is Data Modelling:
-Data modelling is the process of organizing tables and defining relationships between them so power Bi can understand how data connects.
-It work like a map of connections;
.Tables=locations where we assume data is being entered
.Relationships=Roads connecting them as a connecter
.Dax calculations=Directions that rely on the roads being correct
A good model ensures the following in the data:
-Accurate calculations
-Better performance
-Easier report building
-Scalability for large datasets
What is a Schema in power Bi
-A schema describes the structure of your data model-how tables are arranged and connected.
Power Bi typically follows data warehouse schemas,mainly:
1.Star schema
2.Snowflake Schema
3.Flat table(single Table)
1.Star Schema
-The star schema is the most recommended structure in Power Bi.
Structure
.it has:
1.Fact Table(center)
2.Dimension Tables(Around it)
Fact Table:
1.Sales:
-OrderID
-ProductId
-CustomerID
-DateID
-SalesAmount
Dimension Tables
-Products (ProductId,ProductName,Category)
-Customers(CustomerID,CustomerName,Region)
-Date(DateID,Yeah,Month,Day)
Its importance:
.Simple relationships
.Faster performance
.Easier DAX performance
.Clear visuals
Snowflake Schema
-The snowflake schema is a more normalized version of the star schema.
Structure
.Dimensions are split into multiple related tables.e.g
product-categories-subcategories
.This reduces data duplications
.Useful for complex hierarchies
Cardinality
-its how rows match
-ome -to -many(1:*)
one customer -many sales
-one-to-oe
rare
-many-to-many(:)
avoid if possible
Filter Direction(Important)
Single Direction
.Filter flow from dimension-fact
.Prevents confusion
Top comments (0)