It is not easy to give a clear definition of data warehouse (known in English with the term Data Warehousing, DWH). The original description of Bill Inmon, the father of the data warehouse, reads as follows: “The data warehouse consists of the collection of time-oriented, integrated, time-oriented data that are the basis of management decisions” (Inmon, 1992 – own translation). Today it is still the most used description for this concept.
In its original meaning, the data warehouse purely means the storage of information. However, Inmon immediately gives a goal to data collection: making business decisions. This means that data storage is the basis of business intelligence (BI). The close relationship between the two concepts has made the terms data warehouse and business intelligence coexist, but in practice they are often used as synonyms.
In a data warehouse, information is stored from all types of business applications: from document management to human resources and ERP. In principle, a data warehouse does not gather this information by itself. The data cannot be checked in the data warehouse either. However, by making relevant information readily available, it makes all types of reports efficient.
Of course, reports can also be made directly through the ERP. The (limited) reporting modules that many ERP systems offer are also satisfactory for some companies. However, a data store can save a lot of time for those companies that want to gather large-scale data and want to get an overview of their business operations. The central data collection ensures that more holistic analysis can be created. This allows real decisions to be made at the level of business policy and optimize strategies. This general approach is also useful for providing general reports to shareholders.
Finally, the combination of a general image and the detailed information in the data warehouse also helps companies by showing them if they comply with a certain law. For example, when a legislator receives a complaint of poor business management or privacy, he may request certain information. A company that has its data and activities in the data warehouse useful in advance can be better justified and therefore less likely to be wrong.
A data store can be configured in many different ways. The best known models are those of the original Inmon method and the Kimball method. In addition, there is also a newer method called Data Vault. The most suitable method will differ depending on the company.
The Inmon method
The data warehouse’s parent, Inmon, uses a top-down approach. Depending on your model, the design of a data warehouse begins with the overall structure. First, the entire standardized data model is configured, and then the data marts.
Data marts contain specific information for a specific department or for a specific application. Like the data model, these data marts have been standardized. The Inmon method is especially suitable for companies that work following really strict and standardized business processes. In addition, it is a very holistic and structured model. Smaller data marts merge seamlessly into a larger data model. The design and commissioning of the entire model requires more time and investment than the Kimball method, but with this clear classification, the system has relatively little maintenance.