POWER BI

Power BI is a Microsoft business analytics tool that connects to, cleans, and transforms raw data from various sources into interactive, visually immersive reports and dashboards. It enables users to analyze data and create important decisions.
Data modelling is the procedure used by data scientist and engineers to structure data in tables based on relationship and logical framework
Platforms of Power BI
Power BI Desktop: A free, Windows-based application used by data analysts to connect to, model, and visualize data. It is the primary tool for creating reports.
Power BI Service: A cloud-based service (SaaS) used to publish reports, create dashboards, share insights, and collaborate within organizations.
Power BI Mobile Apps: Applications for iOS, Android, and Windows devices to view and interact with reports and dashboards on the go.
Power BI Report Server: An on-premises report server, ideal for companies that cannot store data in the cloud.
A schema defines how data is structured and related, while data modeling is the process of building that structure to ensure performance, accuracy, and usability. The most important schema for Power BI is the star schema.

Types of schemas in power BI

Star Schema: This is the industry standard and recommended approach for Power BI. Consists of a central fact table (containing quantitative measures like sales amounts) surrounded by multiple dimension tables (containing descriptive attributes like product names, dates, or regions).
Advantages: Excellent performance due to fewer joins, simplified DAX calculations, and an intuitive, easy-to-understand model for report authors.
Snowflake Schema: A variation of the star schema where dimension tables are further normalized into sub-dimension tables. For example, a Product dimension might link to a Category table, which then links to a Manufacturer table.
Advantages: Reduces data redundancy and improves data integrity and storage efficiency.
Disadvantages: More complex structure and potentially slower query performance due to more joins compared to a star schema.
Galaxy Schema (Fact Constellation): Involves multiple fact tables that share some common dimension tables, suitable for complex, enterprise-level analysis of different business process

Fact and Dimension Table Overview
Fact Tables-Store transaction data, metrics, and foreign keys such as sale; They are tall, narrow, and grow over time.
Dimension Tables: Store descriptive, categorical data such as Customers. They are short, wide, and used to filter/group data.
Data modelling is important because:

• It creates an organized and reliable roadmap for how data is stored, accessed, and interpreted.

• Effective data storage