Star Schema
A star schema is a dimensional data modeling technique in which a central fact table, holding measurable business events, is directly connected to multiple denormalized dimension tables that provide descriptive context.
9 resources across 2 libraries
Glossary Terms(6)
Database Normalization
Database normalization is the process of organizing tables and columns in a relational database to reduce data redundancy and prevent update, insert, and delet…
OLAP
OLAP (Online Analytical Processing) refers to database systems and workloads optimized for complex, read-heavy analytical queries — aggregations, trends, and m…
Data Mart
A data mart is a focused, subject-oriented subset of a data warehouse, scoped to the needs of a single business function or department such as sales, finance,…
Star Schema
A star schema is a dimensional data modeling technique in which a central fact table, holding measurable business events, is directly connected to multiple den…
Snowflake Schema
A snowflake schema is a dimensional data modeling technique that normalizes dimension tables of a star schema into multiple related sub-tables, reducing data r…
Columnar Database
A columnar database stores data by column rather than by row, allowing analytical queries that scan and aggregate a small number of columns across many rows to…
Interview Questions(3)
Star Schema vs Snowflake Schema: What is the Difference?
A star schema keeps each dimension table fully denormalized in one flat table around a central fact table, while a snowflake schema further normalizes those di…
What Are Fact and Dimension Tables in a Data Warehouse?
A fact table stores the measurable, numeric events of a business process — like sales amount or quantity sold — along with foreign keys to related dimensions,…
OLAP vs OLTP: What is the Difference?
OLTP (Online Transaction Processing) is optimized for many short, concurrent read/write transactions on individual rows, while OLAP (Online Analytical Processi…