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Connecting to Azure Synapse Analytics

This guide provides a step-by-step approach to effortlessly connecting Azure Synapse Analytics with Skypoint AI. The Azure Synapse Connector allows your platform to connect with Azure Synapse Analytics, enabling the ingestion of structured data from Synapse SQL pools. It simplifies data integration by securely extracting data from Synapse tables or views and loading it into your platform for further transformation, reporting, or AI-driven insights. The Azure Synapse Analytics Connector in Skypoint AI enables seamless integration with Azure Synapse Analytics, a cloud-based data warehouse and analytics service. It allows organizations to ingest and synchronize structured data such as transactions, general ledger entries, and vendor records using secure connections. The connector supports service principal authentication, automated scheduling, and data transformation, making it easy to integrate data into Skypoint’s unified data models. This enhances data accessibility, analytics capabilities, and enables AI-driven financial and operational insights.

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Prerequisite

You will need the following details to configure and import data using Azure Synapse Analytics
  • Server Name
  • Database Name
  • Port Number
  • User Name
  • Password

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To Import data using Azure Synapse Analytics

Follow the below steps to create a new dataflow for the Azure Synapse Analytics import connector:
  1. Go to Dataflow > Imports.
Alt image
  1. Click New dataflow.
The Set dataflow name page appears. Alt image
  1. Enter Dataflow name in the Name text area.
  2. Click Next.
The Choose connector page appears. Alt text

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Add Azure Synapse Analytics connector

  1. On the Choose Connector page, use the Search feature to locate and select the Azure Synapse Analytics Connector.
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  1. Enter the Display Name for your dataflow in the text area.
  2. You can add a Description in the text area.
  3. Click Next to proceed.
The Configuration page appears. Alt image

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Connect to the Azure Synapse Analytics account

  1. Fill in the required details on the Configuration page.
  2. Click Connect.
Once the connection is established, you can use the connector to import data from a table in Azure Synapse Analytics. Alt image
  1. Scroll down to the Table Details section, select the checkboxes for the tables you wish to import, and use the dropdown menu to label them as either Data or Metadata.
Alt image :::note In the Table Details section, by default, all tables are selected. You can mark only those tables that you want to import and process the data. For example, to import customer data, you can check those tables which contain customer information, such as name, email, address, and contact details. :::note
ItemDescription
PurposeOption to assign a purpose (Data or Metadata) for each table.
DataLoads customer data
MetadataLoads Metadata
File nameDisplays the name of the file that you imported.
Entity nameDisplays the imported table name by default. You can rename it if required.
  1. Click Save to apply the changes.
Alt image After saving the connection, the Azure Synapse Analytics connector appears on the Dataflow > Imports page.

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Run, edit, and delete the imported data

Once the table is imported, you can execute, modify, and remove the imported table from the Dataflow. Follow the below steps:
  1. Go to the Dataflow > Imports page.
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ItemDescription
NameDisplays the name of the imported Dataflow.
TypeDisplays connector type symbol.
StatusIndicates whether the data is imported successfully.
Tables countDisplays the number of tables imported.
Created DateDisplays date of creation.
Last refresh typeDisplays the refresh value: Full or Incremental.
Updated DateDisplays last modified date.
Last RefreshDisplays the latest refresh date, which updates each time you refresh the data.
Group byOption to view the items in a specific group. For example, type, status, tables count, etc.
  1. Select the horizontal ellipsis under the Actions column and do the following:
If you want toThen
Modify the DataflowSelect Edit and modify the Dataflow. Click Save to apply your changes.
Execute the DataflowSelect Run.
Bring the data to its previous stateSelect Rollback.
Delete the DataflowSelect Remove and then click the Delete button. All tables in the data source get deleted.
See the run history of the DataflowSelect Run history.
Alt image :::note You can see the error message corresponding to failure while importing data from a data source in the Dataflow under Run History > Description. Also, you can see the status, start time, and end time for the execution of the data pipeline. :::

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Next step

After completing the data import, start the Master Data Management (MDM) - Resolve process to create a single, unified view of the data. With SkyPoint MDM, you can ensure that your data is accurate, consistent, and reliable, making it easier to use for business processes, analytics, and reporting.