DatriseAI-first ETL

Azure Table Storage MicroStrategy

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

How Datrise loads Azure Table Storage into MicroStrategy

Datrise syncs Azure Table Storage's records, events, and configuration objects 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 Table Storage: SaaS or API data source for analytics and warehouse sync.

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

How Azure Table Storage entities map to MicroStrategy

Azure Table Storage entityMicroStrategy objectNotes
recordsazure_table_storage_recordsid PK · custom fields → flattened columns
eventsazure_table_storage_eventsdate/time dimensions events
configuration objectsazure_table_storage_configuration_objectsid PK · linked to azure_table_storage_records

FAQ

How does Datrise handle Azure Table 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 Table 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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