Dimensionalization

Dimensionalization refers to the process of assigning dimensions to data. In essence, it is about transforming raw data into a structured format that is suitable for analysis and reporting. This typically involves creating or identifying dimensional tables and fact tables. Dimensional tables, often referred to as dimension tables, store descriptive attributes of the business, such as customer names, product categories, or dates. Fact tables, on the other hand, store the quantitative measures or metrics that are to be analyzed, such as sales figures, order quantities, or website visits.

The goal of dimensionalization is to create a data model that is easy to understand and query, facilitating business intelligence and data warehousing. This process is a key component of dimensional modeling, a design technique used to organize data in a way that optimizes for querying and reporting. The resulting structure often takes the form of a star schema or a snowflake schema, which are optimized for analytical workloads rather than transactional processing. Dimensionalization helps to isolate business processes into understandable units, making it easier for business users to generate reports and gain insights. It is a fundamental step in preparing data for analytical purposes, enabling faster and more efficient data retrieval and analysis.