A data mart is a curated subset of data often generated for analytics and business intelligence users. Data marts are often created as a repository of pertinent information for a subgroup of workers or a particular use case.
What’s the difference between a data mart and a data warehouse?
Slow and overloaded data warehouses are often the underlying reason for the creation of data marts, and frequently serve as their underlying data source. Often, as data volumes and analytics use cases increase, organizations cannot serve every analytics use case without degrading the performance of their data warehouse, so they export a subset of data to the mart for analytics.
Snowflake is the data warehouse that can replace data marts
Snowflake’s innovative data architecture ensures that it can support an unlimited amount of data and users, because new compute resources can be spun up at any time to address new use cases without affecting the other operations that are happening on the database, thus eliminating the need to spin off separate physical data marts in order to maintain acceptable performance.