datamartit

Datamartit is a term used in information technology to denote a pragmatic, IT-centered approach to building datamarts. It emphasizes creating small, subject-specific data stores that serve particular analytic or reporting needs for IT departments or business units.

Overview: Datamartit derives from traditional datamart concepts, with an emphasis on rapid delivery, simplified data models, and closer alignment to user requirements. The data in a datamart is typically pulled from a larger data warehouse, operational systems, or external sources. The goal is to provide fast, reliable access to curated data for targeted analyses.

Architecture: A datamartit typically features a denormalized star or snowflake schema, or even flat tables for simplicity. It relies on ETL or ELT pipelines to extract, transform, and load data into a schema optimized for read performance. It supports self-service BI and ad hoc analysis by designated users.

Governance and security: Even for smaller datamarts, governance includes data quality checks, lineage, metadata, and access control. Data retention and privacy considerations apply, especially when integrating sensitive information.

Deployment: Can be implemented on-premises, in the cloud, or in hybrid environments. Common tools include database platforms, ETL/ELT suites, and BI or analytics tools.

Advantages and challenges: Advantages include faster delivery, lower upfront cost, and tailored analytics. Challenges include potential data duplication, maintenance of multiple datamarts, and integration with enterprise-wide governance.

See also: Data mart, Data warehouse, Business intelligence, ETL.