DatriseAI-first ETL

Zendesk Chat Azure Synapse

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

How Datrise loads Zendesk Chat into Azure Synapse

Datrise syncs Zendesk Chat's chats, agents, visitors, departments, and response times 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

Zendesk Chat: Live chat conversations and agent performance.

Azure Synapse: Microsoft analytics workspace with SQL pools.

How Zendesk Chat entities map to Azure Synapse

Zendesk Chat entityAzure Synapse objectNotes
chatszendesk_chat_chatsid PK · custom fields → NVARCHAR(MAX) JSON columns
agentszendesk_chat_agentsid PK · linked to zendesk_chat_chats
visitorszendesk_chat_visitorsid PK · linked to zendesk_chat_chats
departmentszendesk_chat_departmentsid PK · linked to zendesk_chat_chats

FAQ

How does Datrise handle Zendesk Chat'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 Zendesk Chat 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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