A Comprehensive Guide to Data Warehouse Architecture in 2023: Components, Design, and Best Practices

Data warehouses play a critical role in modern businesses, providing a centralized repository for data storage, management, and analysis. To build an efficient data warehouse, it is essential to understand its underlying architecture and design principles. This comprehensive guide will explore data warehouse architecture, its components, design considerations, and best practices to help you create a robust and effective data warehouse in 2023.

Data Warehouse Architecture: Overview

Data warehouse architecture refers to the design and organization of various components that make up a data warehouse, enabling efficient data storage, management, and analysis. A typical data warehouse architecture consists of the following layers:

a. Data Sources b. Data Integration and ETL c. Data Storage d. Metadata e. Data Access and Analytical Tools

Data Sources

Data sources are the systems and platforms that provide raw data to the data warehouse. These can include:

a. Transactional databases: Relational databases containing transactional data from business operations, such as sales, inventory, and customer interactions.