What Is a Data Mart?
A data mart is a focused slice of a data warehouse, organized around a single subject area, finance, sales, inventory, or one department’s needs. Where a data warehouse holds enterprise-wide data across every subject, a data mart narrows that to the data one group actually uses, structured the way that group thinks about it. The result is a smaller, simpler, faster store tailored to a specific audience.
Why Data Marts Exist
A full enterprise warehouse can be large and complex, with far more data than any one team needs. A data mart solves that by giving a department its own curated view: the finance mart holds the financial data modeled for finance, the sales mart holds sales data modeled for sales. Queries run faster because the dataset is smaller, the structure is easier to understand because it is scoped to one subject, and teams can work without wading through the whole enterprise model.
Data Mart vs Data Warehouse
The two are related and often confused. A data warehouse is the broad, enterprise-wide repository that integrates data from across the business. A data mart is a subset of that, focused on one subject or department. A useful way to picture it: the warehouse is the whole library; a data mart is the shelf for one topic. Data marts are usually built from the warehouse, drawing on its governed, integrated data rather than pulling from source systems separately.
Dependent vs Independent Data Marts
Data marts come in two forms. A dependent data mart is built from an existing data warehouse, inheriting its clean, conformed data. An independent data mart is built directly from source systems, standing on its own. Dependent marts are generally preferred, because they stay consistent with the enterprise model; independent marts are faster to stand up but risk becoming yet another disconnected silo with its own version of the numbers.
Data Marts in a Modern Foundation
In a lakehouse, the idea of a data mart lives on as a curated, subject-focused layer modeled for a specific audience, often the gold layer for one department. The principle is the same: give each team a clean, governed view scoped to what it needs, built on top of the shared foundation rather than separate from it. QuickLaunch builds that governed foundation for JD Edwards, Vista, NetSuite, and OneStream and models subject-focused, report-ready data on top, so each team gets its tailored view without creating a disconnected silo.
Frequently Asked Questions
What is a data mart?
A subject-focused subset of a data warehouse, built to serve one team, department, or business area. It holds the data that group needs, modeled the way they use it, in a smaller and faster store than the full warehouse.
What is the difference between a data mart and a data warehouse?
A data warehouse is the enterprise-wide repository integrating data from across the business. A data mart is a subset of it focused on one subject or department. The warehouse is the whole library; the mart is the shelf for one topic.
What is the difference between dependent and independent data marts?
A dependent data mart is built from an existing data warehouse and inherits its conformed data. An independent data mart is built directly from source systems and stands alone, which is faster to create but risks becoming a disconnected silo.
