What Is a Data Model?

A data model defines the relationships between data points, useful in software development, data migration and system integration. Data models can be used to design new systems and software. In business intelligence, they can help database architects and data analysts gain insight into company data and its attributes, and set parameters for data grouping, sorting, storing, and formatting.

The purpose of a data model is to help communicate the computer system’s requirements, interactions with the data, and potential outcomes. Building a data model specific to the needs of each individual organization helps reduce errors, encourage consistency, save time, improve database performance, and develop communication between teams.

Types of data models

Data models can be classified into three main categories based on the data’s abstraction levels (from lowest to highest abstraction):

1. Physical: A physical data model provides a specific blueprint of how the database will store data, helping technicians accurately create the design.

2. Logical: A logical data model omits technical specifications but includes essential details, such as data attributes, relationships, constraints, and subtypes. They can be applied to more than one database or system, meaning you could replicate the model for various products.

3. Conceptual: A conceptual data model offers a big-picture view of the system’s content and structure. It can also serve as a starting point for designing logical and physical models.

Data modeling and data analytics

Data modeling helps analysts visualize data and set parameters to gain insights that enable making strategic business decisions. It also helps incorporate formulas, currencies, and data hierarchy for easier manipulation. Data models transform raw data into actionable insights.

Related terms

• Data integrity

• Data analytics

• Structured data

• Unstructured data

• Business intelligence

Learn more about data analytics

Ready to learn more about data models to start a career in data analytics? Consider completing the Google Data Analytics Professional Certificate. This eight-course series is appropriate for beginners that want to learn skills like data analysis, data visualization, data ethics, and data collection.