DatriseAI-first ETL

Azure Blob Storage to MicroStrategy Integration

AI-first ETL from Azure Blob Storage into MicroStrategy. Governed entities, incremental sync, typed landing tables.

How Datrise loads Azure Blob Storage into MicroStrategy

Datrise syncs Azure Blob Storage's containers, blobs, blob metadata, snapshots, access tiers, and blob versions into MicroStrategy as warehouse tables for MicroStrategy's schema objects. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date/time dimensions.

Sync is incremental: Datrise uses incremental refresh of the warehouse tables behind attributes and metrics, so re-runs update only what changed. Date-partitioned facts. MicroStrategy maps attributes to columns, so Datrise lands stable keys and names so metrics don't break.

Ideal for large-scale enterprise reporting and governance.

Endpoints

Azure Blob Storage: Object storage for blobs and data lake files on Azure.

MicroStrategy: Enterprise BI with dossiers, governed metrics, and mobility.

How Azure Blob Storage entities map to MicroStrategy

Azure Blob Storage entityMicroStrategy objectNotes
containersazureblobstorage_containersid PK · custom fields → flattened columns
blobsazureblobstorage_blobsid PK · linked to azureblobstorage_containers
blob metadataazureblobstorage_blob_metadataid PK · linked to azureblobstorage_containers
snapshotsazureblobstorage_snapshotsid PK · linked to azureblobstorage_containers

FAQ

How does Datrise handle Azure Blob Storage's custom fields in MicroStrategy?

Flexible values are stored as flattened columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native MicroStrategy types.

How does the Azure Blob Storage to MicroStrategy sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the warehouse tables behind attributes and metrics.

Related pipelines

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