Introduction
BI analysts are tasked with answering business questions for their clients. Before answering questions concerning revenue, profits, or growth prospects, an analyst needs to understand where the data is stored and how to bring them together. And here is where relationship schemas and joins come in. Data is usually not stored in one place. It is spread across multiple sheets originating from different systems, such as CRM records, POS systems, marketing campaigns, or off-system sales.
Relationship databases are made of two core concepts: relationship schemas and joins. Relationship Schemas is the framework on what data a given systems store and how the different sections of the data connect. Meanwhile, Joins is the means by which an analyst can query the connections established by relationship schemas. Ultimately, the latter creates the full picture of the data and answers business questions.
What is a Relationship Schema?
A relationship schema is a description of how data is structured. It describes the structure of each table and how the different tables relate to one another. A schema is more of the skeleton or structure for where data is stored and how the different information relates or connects. In addition, it is a map that tells you that a certain table exists and what columns the different tables hold and how these tables connect.
