What is a data mart?

A data mart narrows a warehouse down to one department's world. Rather than making the finance team wade through the entire enterprise model, a finance data mart holds just the tables and metrics finance cares about, often modelled dimensionally for quick reporting.

Data marts are used to:

• Simplify give a team only the data relevant to them.
• Speed up smaller, focused datasets query faster.
• Tailor model the data around one domain's needs.

They can be carved from a central warehouse (dependent) or built directly from sources (independent). Either way, they are another modelled dataset to design and maintain.

iDBQuery gives teams a data-mart-like focus without building one. Each team can connect the sources relevant to them and ask plain-language questions scoped to their domain, finance, sales, operations, while iDBQuery handles the joins and definitions behind the scenes. With role-based access you control who sees what, so a department effectively gets its own governed, self-serve view. And when a question needs to reach beyond the department, iDBQuery's federation can pull in other sources on demand, something a fixed data mart cannot do, always returning cited answers traced to source rows.