Import MailChimp Data Using Azure Data Factory

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Use CData Connect Cloud to connect to MailChimp from Azure Data Factory and import live MailChimp data.

Azure Data Factory (ADF) is a fully managed, serverless data integration service. When paired with CData Connect Cloud, ADF provides instant, cloud-to-cloud access to MailChimp data in data flows. This article demonstrates how to connect to MailChimp using Connect Cloud and access MailChimp data in ADF.

CData Connect Cloud provides a pure cloud-to-cloud interface for MailChimp, allowing you to access data from live MailChimp data in Azure Data Factory — without replicating the data to a natively supported database. Using optimized data processing out of the box, CData Connect Cloud pushes all supported SQL operations (filters, JOINs, etc.) directly to MailChimp, leveraging server-side processing to return the requested MailChimp data quickly.

Connect to MailChimp in Connect Cloud

CData Connect Cloud uses a straightforward, point-and-click interface to connect to data sources.

  1. Log into Connect Cloud, click Connections and click Add Connection
  2. Select "MailChimp" from the Add Connection panel
  3. Enter the necessary authentication properties to connect to MailChimp.

    You can set the APIKey to the key you generate in your account settings, or, instead of providing your APIKey, you can use the OAuth standard to authenticate the application. OAuth can be used to enable other users to access their own data. To authenticate using OAuth, you will need to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL by registering an app with MailChimp.

    See the "Getting Started" chapter in the help documentation for a guide to using OAuth.

  4. Click Create & Test
  5. Navigate to the Permissions tab in the Add MailChimp Connection page and update the User-based permissions.

Add a Personal Access Token

If you are connecting from a service, application, platform, or framework that does not support OAuth authentication, you can create a Personal Access Token (PAT) to use for authentication. Best practices would dictate that you create a separate PAT for each service, to maintain granularity of access.

  1. Click on your username at the top right of the Connect Cloud app and click User Profile.
  2. On the User Profile page, scroll down to the Personal Access Tokens section and click Create PAT.
  3. Give your PAT a name and click Create.
  4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured, you are ready to connect to MailChimp data from Azure Data Factory.

Access Live MailChimp Data in Azure Data Factory

To establish a connection from Azure Data Factory to the CData Connect Cloud Virtual SQL Server API, follow these steps.

  1. Login to Azure Data Factory.
  2. If you have not yet created a Data Factory, Click New -> Dataset.
  3. In the search bar, enter SQL Server and select it when it appears. On the following screen, enter a name for the server. In the Linked service field, select New.
  4. Enter the connection settings.
    • Name - enter a name of your choice.
    • Server name - enter the Virtual SQL Server endpoint and port separated by a comma: tds.cdata.com,14333
    • Database name - enter the Connection Name of the CData Connect Cloud data source you want to connect to (for example, MailChimp1).
    • User Name - enter your CData Connect Cloud username. This is displayed in the top-right corner of the CData Connect Cloud interface. For example, test@cdata.com.
    • Password - select Password (not Azure Key Vault) and enter the PAT you generated on the Settings page.
    • Click Create.
  5. In Set properties, set the Name, choose the Linked service we just created, select a Table name from those available, and Import schema from connection/store. Click OK.
  6. After creating the linked service, the following screen should appear:
  7. Click preview data to see the imported MailChimp table.
  8. You can now use this dataset when creating data flows in Azure Data Factory.

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