DatriseAI-first ETL

Freshcaller to Azure Synapse Integration

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

How Datrise loads Freshcaller into Azure Synapse

Datrise syncs Freshcaller's calls, agents, queues, phone numbers, call metrics, and recordings 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

Freshcaller: Cloud call center for support and sales.

Azure Synapse: Microsoft analytics workspace with SQL pools.

How Freshcaller entities map to Azure Synapse

Freshcaller entityAzure Synapse objectNotes
callsfreshcaller_callsid PK · custom fields → NVARCHAR(MAX) JSON columns
agentsfreshcaller_agentsid PK · linked to freshcaller_calls
queuesfreshcaller_queuesid PK · linked to freshcaller_calls
phone numbersfreshcaller_phone_numbersid PK · linked to freshcaller_calls

FAQ

How does Datrise handle Freshcaller'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 Freshcaller 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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