Dynamics 365 FO (Dataverse via Synapse Link)

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Connector Details

Connector AttributesDetails
NameDynamics 365 FO (Dataverse via Synapse Link)
DescriptionDynamics 365 Finance and Operations (FO) Synapse Link is a transformative integration that connects Dynamics 365 FO with Azure Synapse Analytics, enabling organizations to seamlessly analyze and derive insights from their financial and operational data. By leveraging Synapse Link, businesses can unlock the full potential of their Dynamics 365 FO data by integrating it with Azure Synapse Analytics, a powerful analytics service. This integration facilitates real-time data ingestion, processing, and analysis, empowering organizations to gain deeper insights into financial performance, supply chain efficiency, and operational effectiveness. With Dynamics 365 FO Synapse Link, organizations can make data-driven decisions, optimize business processes, and drive operational excellence across the enterprise.
Connector TypeClass D

Features

Feature NameFeature Details
Load StrategiesFull Load, Incremental Load
Metadata ExtractionSupported
Data AcquisitionSupported
Data PublishingNot Supported
Automated Schema Drift HandlingNot Supported

Source Connection Attributes

Connection ParametersData TypeExample
Connection NameStringDynamics365FOConnector
Azure Data Lake Access KeyStringyour-adl-access-key
Storage Account NameStringyour-storage-account
Storage Container NameStringyour-storage-container
Bronze Schema (Optional)String
Silver Schema (Optional)String

Connector Specific Configuration Details

  1. Dynamics 365 FO (Dataverse via Synapse Link) connector has optional values such as Bronze Schema and Silver Schema

  2. Incremental extraction is supported in the connector. The incremental step has been optimized to identify the table partitions that could contain incremental data by comparing the watermark start date to the modified times of the files.

  3. An incremental extraction should use the sinkmodifiedon column as the watermark and the id and versionnumber columns as the candidate key.

  4. Occasionally, the extraction will fail while reading a CSV file. Previously, it was thought this was due to corrupt files, but further investigation shows that this happens most frequently on high-traffic tables meaning the problem is a simultaneous read/write. To approach this, the connector will attempt a second read of the source data after 20 seconds. This should mitigate but will not remove the problem entirely. Future optimization might attempt to identify when the files are actively being written.

  5. More details around this connector

Screenshot To Use Connector

Updated about 2 months ago