Employing SQL and Dimensional Modeling To Optimize Datasets for BI tools
Simply put, dimensional modeling is all about separating your data between entities and events pertaining to those entities. Three fundamental concepts are dimension tables, fact tables, and measures. Fact tables: a stack of data that characterizes business events (a fact). It bears connections to measures and dimensions to pull out additional details. Measures: numeric characteristics of the fact table. It may perhaps be calculations, or simply values pertaining to an event. Furthermore, helps with questions that can be answered via numbers for example: How much? At which rate? Dimension tables: entities that reply to clear-cut business questions about the fact table: Who? What? Where? When? Why? How can dimensional modeling help us to reduce datasets? Easy! Imagine if you needed to get all of this data from a single source. It will be a large table, right? With SQL server dimensional modeling you are compressing the amount of repeated information. As a result, yo...