DatriseAI-first ETL

CSV File to MicroStrategy Integration

AI-first ETL from CSV File into MicroStrategy. Governed entities, incremental sync, typed landing tables.

How Datrise loads CSV File into MicroStrategy

Datrise syncs CSV File's rows, columns, headers, delimiters, file batches, and encodings 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

CSV File: Delimited flat files from exports and drops.

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

How CSV File entities map to MicroStrategy

CSV File entityMicroStrategy objectNotes
rowscsv_file_rowsid PK · custom fields → flattened columns
columnscsv_file_columnsid PK · linked to csv_file_rows
headerscsv_file_headersid PK · linked to csv_file_rows
delimiterscsv_file_delimitersid PK · linked to csv_file_rows

FAQ

How does Datrise handle CSV File'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 CSV File 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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