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Last updated: Sep 29, 2026 09:29 UTC

Microsoft Azure Synapse

Azure Synapse Analytics is a unified analytics platform that combines data warehousing, big data processing (via Apache Spark), and log/timeseries analysis. It brings together SQL, Spark, and Data Explorer capabilities into a single workspace—helping organizations analyze data efficiently and at scale.

Prerequisites

Ensure the following requirements are met before you connect Azure Synapse as a data source:

  • ADOC access & permissions to add data sources.
  • An existing data plane in ADOC or create one for Azure Synapse Analytics ingestion. See the Data Plane Installation documentation for more information.
  • Azure Synapse workspace details, including:
    • Workspace name
    • SQL Pool configuration (e.g., Dedicated SQL Pool)
    • Authentication credentials (SQL user/password, Managed Identity, or Service Principal)

Add Azure Synapse Analytics as a Data Source

Step 1: Start Setup

  • Navigate to the left main navigation menu, click Control Center -> Integrations.
  • From the Integrations page, click Add Data Source and select Azure Synapse Analytics from the list of data sources.
  • On the Data Source Details page:
    • Enter a Data Source Name and optional Description for the data source.
  • Ensure the Data Reliability toggle is enabled and select a data plane.
  • Click Next.

Step 2: Add Connection Details

  • Enter your Azure Synapse workspace name.
  • Select a SQL Pool configuration method (currently, Dedicated SQL Pool Name is supported).
  • Authentication options:
    • Username & Password: Provide the SQL Pool name, username, and password.
    • Managed Identity (optional): Use for secure Azure credential-based access. If enabled, assign a Managed Identity to access Synapse via Azure credentials.
    • Service Principal (optional): Use for Azure AD-based authentication with Client ID, Client Secret, and Tenant ID.
    • Secret Manager (optional): Use when storing credentials in a secure secret store. Provide workspace, SQL Pool details, username, and secret configuration details.
  • Select the Data Plane Engine: Choose either Spark or Pushdown for better performance during profiling and checks.
  • Click Test Connection. If successful, proceed. Otherwise, double-check your entries and network connectivity.
  • Click Next to proceed to configure observability.

Step 3: Set Up Observability

  • Set a scan schedule, including frequency and time zone, so ADOC can crawl Synapse for metadata and quality metrics.
  • Enable Notifications for crawler success or failure alerts.
  • Click Submit to finalize the setup.

Troubleshooting

1. Connection Error After Test Connection

  • Issue: ADOC fails to connect.
  • Solution: Verify workspace and SQL Pool names, authentication credentials, firewall settings, and whether you're using the correct Data Plane Engine.

2. Performance Slowness in Profiling

  • Issue: Profiling or data checks take too long.
  • Solution: Switch to Pushdown engine for faster execution using Synapse’s native compute.

3. Freshness Metrics Not Visible

  • Issue: No freshness or data latency information shows up.
  • Solution: Use a Row Count Check as a proxy metric for freshness, or rely on external solutions like ADF (Azure Data Factory) SLAs.

What’s Next

  • Profile your Azure Synapse Analytics data source to begin applying Data Reliability policies.
  • Create and apply observability policies: Define Data Quality, Schema Drift, and Anomaly Detection checks. (No dashboards until policies are in place.)
  • Configure alerts: Proactively notify your team on quality or pipeline issues.