Datawarehouse: Kimball vs Inmon Approach

A comparison of the Kimball and Inmon approaches in Datawarehousing.

Ralph Kimball and Bill Inmon are two well-known figures in the field of data warehousing. Their approaches to design and architecture have significantly influenced the development of data warehousing systems. This article discusses their approaches to Data warehousing.

What is a Datawarehouse?

A data warehouse system is used for storing, analyzing, and retrieving large amounts of data. It is designed to support the efficient querying and analysis of data and is often used to support business intelligence and data analytics applications.

A warehouse typically stores data from various sources, such as transactional databases, log files, and external data sources. It is designed to be optimized for fast querying and data analysis and may incorporate features such as indexes, materialized views, and partitioning to improve performance.

Data warehouses are typically built using specialized software and hardware. They may be implemented using a variety of architectures, such as a traditional three-tier architecture or a hybrid architecture that combines on-premises and cloud-based components.

Kimball Approach

The Kimball approach, also known as the dimensional modeling approach, emphasizes using a data warehouse design based on the concept of a “fact table” surrounded by associated “dimension tables.” This design intends to support fast querying and data analysis using a star or snowflake schema. The Kimball approach also emphasizes the importance of designing the data warehouse for the needs of the business users and of using a bottom-up, iterative approach to design and development.

Kimball’s approach is always focused on the bottom-up procedure. When developing a data warehouse using the Kimball approach, the first requirement is to identify the critical business processes and the business questions that will satisfy by the data warehouse. So Key sources of data for the warehouse need to be analyzed and documented. Data is gathered from all the different sources and loaded into a staging area using ETL software. Data is then fed into a…