Data Integration

Mimasa AI connects to the databases, warehouses and file- or API-based sources most commonly used across engineering and analytics teams, and additional source types are added over time. Each connection is configured once at the workspace level and then made available to any chart, dashboard or workflow that needs it, avoiding duplicate setup for the same underlying system. The set of currently supported sources is visible from the data sources section of the workspace.

For sources that need transformation before they are analysis-ready, workflows can be used to extract data, apply transformations, and load the result back into a destination the platform can query. This lets teams standardize cleaning and enrichment logic in one place rather than repeating it in every chart that touches the raw data. Scheduled workflows keep these transformed datasets current without manual intervention.

When connecting a new source, field names and types from the source system are mapped to the fields used in Mimasa AI, which is what allows charts and reports to reference data consistently regardless of where it originated. Mapping can be adjusted if a source schema changes, and mismatched or renamed fields will surface clearly rather than failing silently. Keeping mappings well documented makes it easier for teammates to build correctly on top of a shared source.