Databases Intermediate

What is Data Warehouse?

A centralized repository optimized for analytical queries that integrates data from multiple operational sources.

Data warehouses are optimized for read-heavy analytical workloads (OLAP) rather than transactional operations (OLTP). They use columnar storage, star/snowflake schemas, and materialized views for fast aggregation queries.

Popular solutions include Snowflake, BigQuery (Google), Redshift (AWS), and Azure Synapse. Data warehouses typically receive data via ETL/ELT processes and serve business intelligence tools, dashboards, and ad-hoc analysis.

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Related Terms

Write-Ahead Log (WAL)

A technique where changes are first written to a log before being applied to the database, ensuring crash recovery and data integrity.

Database Constraint

Rules enforced by the database to maintain data integrity, including NOT NULL, UNIQUE, CHECK, PRIMARY KEY, and FOREIGN KEY.

A database object that automatically executes a specified function when certain events (INSERT, UPDATE, DELETE) occur on a table.

Query Optimization

The process of improving database query performance through indexing, query rewriting, and schema design techniques.

Row-Level Security (RLS)

A database feature that restricts which rows a user can access in a table based on security policies.

A virtual table defined by a SQL query that provides a simplified or restricted view of data from one or more tables.

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