Data Warehouse

Interview Questions

A data warehouse is a centralized repository that integrates and stores data from various sources to support business intelligence and reporting.
The primary purpose of a data warehouse is to provide a unified and consistent view of data for reporting and analysis to support decision-making processes.
ETL (Extract, Transform, Load) is the process of extracting data from source systems, transforming it to meet business requirements, and loading it into a data warehouse.
A database is typically used for transactional processing, while a data warehouse is designed for analytical processing and reporting.
A data mart is a subset of a data warehouse that focuses on a specific business function or department and is designed for the needs of a particular group of users.
In a star schema, a central fact table is connected to dimension tables, while in a snowflake schema, dimension tables are normalized into multiple related tables.
OLAP (Online Analytical Processing) allows users to interactively analyze and explore multidimensional data for better insights.
Slowly changing dimensions (SCDs) represent how data changes over time and are categorized into different types to handle historical data in a data warehouse.
Data warehousing architecture includes components like data sources, ETL processes, data storage, metadata, and tools for reporting and analysis.
Data quality is crucial in a data warehouse to ensure that the information used for reporting and analysis is accurate, complete, and consistent.

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