Dimensionalisierung

Dimensionalisierung refers to the process of defining and assigning dimensions to data. In data warehousing and business intelligence, dimensionalization is a fundamental step in creating a dimensional model, which is optimized for querying and analysis. This involves identifying key business entities, such as customers, products, and time, and then structuring the data around these entities into facts and dimensions.

Facts represent the measurements or metrics of a business process, like sales revenue or website visits. Dimensions provide the context for these facts, answering questions like "who," "what," "when," and "where." For example, a "sales" fact table might be linked to "customer," "product," and "date" dimension tables. The process of dimensionalization requires understanding the business requirements and translating them into a logical data model.

Proper dimensionalization leads to a more intuitive and efficient data structure for reporting and analysis. It simplifies the process of slicing and dicing data, allowing users to explore trends and gain insights without complex SQL queries. Conversely, poorly dimensionalized data can result in performance issues and make it difficult to derive meaningful information. The goal is to create a model that is both easy to understand and performant for analytical workloads.