Kimball offered the first alternative to the traditional Inmon method: a bottom-up approach. This does not initially involve a standardized data store. Instead, it first focuses on the collection of real data. Then, the data is divided into data marts. The structure of both data marts and larger data models depends, therefore, on the type of data that a company wants to gather. The Kimball method is especially chosen by companies that want to be fast at the operational level and who do not want or can face a large investment. In addition, it is a more flexible working method, since the superior model is influenced by data marts. The biggest drawback that companies find with this method is that a general structure is missing.
Data vault, developed by Dan Linstedt, is the newest and perhaps the most complicated way to carry out a data warehouse. This model combines all forms of data collection and also connects them in various ways between them. The data vault model consists of three components…
The hubs found within the data vault are tables that represent the business entity. For example, the commercial entity may be a “customer”, “product” or “warehouse”. The entity can be identified through a unique code number and with its different names.
The links represent relationships or transactions between the hubs. In this way, the relationship between a product and the warehouse can indicate the level of inventory. The transaction that occurs between a product and the customer is a buying action.
Satellites complete the data model. They add very relevant information about the hub or link. For example, this may refer to customer location data, special discounts, etc.
What makes the data vault even more complicated is that the data comes from different sources and comes in different versions. All data is saved as recorded. Therefore, the responsibility for the reliability of the data rests with the source. Historical data is also saved. Therefore, an update of some data does not eliminate its previous versions.
Often, the data vault method is implemented by companies that want to offer their data in a very dynamic way and that attach great importance to the underlying relationships. Actually, Data Vault goes far beyond the data warehouse. The information design is responsible for directly providing interpretations that are usually more technically covered by business intelligence (BI).