A data mart is a subset of a data warehouse designed to serve a specific business function or team. Instead of containing all enterprise data, a data mart focuses on a particular domain such as sales, marketing, finance, or operations.

For example:

• A sales data mart may include leads, opportunities, and revenue

• A marketing data mart may include campaign data and web analytics

• A finance data mart may include billing, expenses, and forecasts

Data marts make analytics faster and more accessible by reducing complexity. Teams can query relevant data without navigating enterprise-wide datasets.

There are two common types:

• Dependent data marts (built from a central warehouse)

• Independent data marts (built directly from source systems)

Dependent data marts are preferred in modern architectures because they maintain consistency while improving usability.

Data marts improve:

• Performance

• Team-specific insights

• Security and access control

• Development speed

However, poorly governed data marts can create silos and inconsistencies. This is why centralized governance and shared metric definitions are important.

In BI systems, data marts balance specialization and standardization, enabling teams to move fast without sacrificing data trust.