Explain the difference between Kimball, Inmon and Data Vault

The Kimball and Inmon methodologies are two different approaches to data warehouse design that have been developed over the years.

The Kimball methodology, developed by Ralph Kimball, is based on the idea of a “data mart,” which is a subset of a larger data warehouse that is designed to meet the specific needs of a particular business unit or department. In this approach, data marts are designed and implemented incrementally, with each data mart serving a specific business function or area.

The Inmon methodology, developed by Bill Inmon, takes a different approach to data warehouse design. In this approach, the data warehouse is seen as a central repository of all the data an organization needs to make informed decisions. The Inmon methodology emphasizes the importance of understanding the business requirements before designing the data warehouse, and suggests that all data should be stored in a single, centralized location.

Data Vault is a data modeling technique that was developed by Dan Linstedt. It is based on the idea of creating a central “data vault” that stores all of an organization’s historical data in a standardized, easy-to-access format. The Data Vault approach focuses on storing data in a flexible, scalable way that allows for easy updates and modifications over time. It is often used in conjunction with other data modeling techniques, such as the Kimball or Inmon methodologies.