> ## Documentation Index > Fetch the complete documentation index at: https://docs.skypoint.ai/llms.txt > Use this file to discover all available pages before exploring further. # # Connecting to Azure Synapse Analytics This guide provides a step-by-step approach to effortlessly connecting Azure Synapse Analytics with skyData. 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 skyData 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. ## Prerequisite You will need the following details to configure and import data using [Azure Synapse Analytics](https://azure.microsoft.com/en-us/products/synapse-analytics/?msockid=1a11f2b867a16f663b53e74266c36eee) * Server Name * Database Name * Port Number * User Name * Password ## 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 2. Click **New dataflow**. The **Set dataflow name** page appears. Alt image 3. Enter **Dataflow name** in the **Name** text area. 4. Click **Next**. The **Choose connector** page appears. Alt text ## Add Azure Synapse Analytics connector 1. On the **Choose Connector page**, use the Search feature to locate and select the **Azure Synapse Analytics** Connector. Alt image 2. Enter the **Display Name** for your dataflow in the text area. 3. You can add a **Description** in the text area. 4. Click **Next** to proceed. The **Configuration** page appears. Alt image ## 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 3. 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 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. | Item | Description | | :---------- | :-------------------------------------------------------------------------- | | Purpose | Option to assign a purpose (Data or Metadata) for each table. | | Data | Loads customer data | | Metadata | Loads Metadata | | File name | Displays the name of the file that you imported. | | Entity name | Displays the imported table name by default. You can rename it if required. | 5. Click **Save** to apply the changes. Alt image After saving the connection, the Azure Synapse Analytics connector appears on the **Dataflow** > **Imports** page. ## 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. Alt image | Item | Description | | :---------------- | :------------------------------------------------------------------------------------------ | | Name | Displays the name of the imported Dataflow. | | Type | Displays connector type symbol. | | Status | Indicates whether the data is imported successfully. | | Tables count | Displays the number of tables imported. | | Created Date | Displays date of creation. | | Last refresh type | Displays the refresh value: Full or Incremental. | | Updated Date | Displays last modified date. | | Last Refresh | Displays the latest refresh date, which updates each time you refresh the data. | | Group by | Option to view the items in a specific group. For example, type, status, tables count, etc. | 2. Select the horizontal ellipsis under the **Actions** column and do the following: | If you want to | Then | | :----------------------------------- | :------------------------------------------------------------------------------------------------- | | Modify the Dataflow | Select **Edit** and modify the Dataflow. Click **Save** to apply your changes. | | Execute the Dataflow | Select **Run**. | | Bring the data to its previous state | Select **Rollback**. | | Delete the Dataflow | Select **Remove** and then click the **Delete** button. All tables in the data source get deleted. | | See the run history of the Dataflow | Select **Run history**. | Alt image 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. ## Next step After completing the data import, start the [Master Data Management (MDM) - Resolve](https://docs.skypointcloud.com/docs/stitch.html) 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.