DatriseAI-first ETL

Harvest Forecast to Azure Synapse Integration

AI-first ETL from Harvest Forecast into Azure Synapse. Governed entities, incremental sync, typed landing tables.

How Datrise loads Harvest Forecast into Azure Synapse

Datrise syncs Harvest Forecast's assignments, people, projects, clients, milestones, and scheduled hours into Azure Synapse as a typed table per source entity. Flexible or custom fields land in NVARCHAR(MAX) JSON columns, and timestamps such as created, updated, and status changes are typed as datetime2.

Sync is incremental: Datrise uses COPY into staging, then a MERGE on stable id, so re-runs update only what changed. Hash distribution on the join id with date partitioning on facts. Synapse dedicated pools reward good hash-distribution choices, so Datrise distributes on entity ids to avoid data-movement-heavy joins.

Ideal for Azure analytics estates feeding Power BI.

Endpoints

Harvest Forecast: Resource scheduling and project capacity planning.

Azure Synapse: Microsoft analytics workspace with SQL pools.

How Harvest Forecast entities map to Azure Synapse

Harvest Forecast entityAzure Synapse objectNotes
assignmentsharvest_forecast_assignmentsid PK · custom fields → NVARCHAR(MAX) JSON columns
peopleharvest_forecast_peopleid PK · linked to harvest_forecast_assignments
projectsharvest_forecast_projectsid PK · linked to harvest_forecast_assignments
clientsharvest_forecast_clientsid PK · linked to harvest_forecast_assignments

FAQ

How does Datrise handle Harvest Forecast's custom fields in Azure Synapse?

Flexible values are stored as NVARCHAR(MAX) JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Azure Synapse types.

How does the Harvest Forecast to Azure Synapse sync stay up to date?

It runs incrementally — Datrise uses COPY into staging, then a MERGE on stable id.

Related pipelines

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