Data Modelling

What is data modeling?

Data modeling is the process of creating a simplified visual diagram of a software system and the data elements it contains, using text and symbols to represent the data and how it flows. Data models provide a blueprint to businesses for designing a new database or reengineering a legacy application. Overall, data modeling helps an organization use its data effectively to meet business needs for information.

A data model can be thought of as a flow chart that illustrates data entities, their attributes and the relationships between entities. Its goal is to show the types of data in a system, its formats and attributes, relationships between data types and how they can be organized. Data modeling enables data management and data analytics teams to document data requirements for applications and identify errors in development plans before any code is written.

Data modeling is created using text, symbols and diagrams. It is typically built around business and application requirements, and additional feedback is gathered from end users and stakeholders. These are then translated into structures that create a database design. The data itself can be modeled at different levels of abstraction. Data models are also expected to change over time along with business needs.

Alternatively, data models can be created through reverse-engineering efforts that extract them from existing systems. That's done to document the structure of relational databases that were built on an ad hoc basis without upfront data modeling and to define schemas for sets of raw data stored in data lakes or NoSQL databases to support specific analytics applications.