This often creates redundancy and a lack of clarity. At best, the provider might make strong assumptions about the specific metrics their users will want, and organize their data models accordingly. Instead, most data sources deliver data in whatever structure is most expedient from the perspective of the SaaS provider. Engineers who design and build API feeds seldom approach issues in the way that analysts do.

These benefits free analysts to focus on modeling and transforming data in order to produce reports and dashboards.Ī schema is useful because raw data from an application or an operational system is seldom analytics-ready. It provides analysts with a clear, easily understood starting point for analytics projects. It absolves analysts of the need to reverse-engineer the underlying data model of an application. It largely removes cleaning and other preprocessing from the analyst’s workflow. Whether in an application or a data warehouse, a well-designed database schema clearly organizes data into distinct entities with their appropriate attributes, shows the interrelationships between entities, and imposes constraints such as data types.Ī well-designed schema in a data warehouse makes life easier for analysts in the following ways: Here, we will discuss the importance of schemas in the context of data integration and analytics. This ensures that your data can be easily understood and turned into dashboards and reports by your analysts. When a data pipeline extracts and loads data into a data warehouse, it performs preprocessing, such as cleaning and normalization, to make the data consistent and legible, and then populates the schema. Since data warehouses are a type of database, data stored in a data warehouse must also be organized into schemas. Schemas are important to data integration and analytics, as well. A logical database schema translates that data model into something that is suited for storage in a relational database.

Simply put, a database schema is a blueprint that organizes data into tables with columns, keys and interrelations.Įvery application contains a representation of reality called a “ data model” that specifies what data is necessary to the functioning of the application, as well as how users interact with it.

What is a database schema