Azure Data Lake

Azure Data Lake is a scalable cloud storage service designed for big data analytics and large-scale data processing.

Frends offers seamless integration with Azure Data Lake, enabling you to effortlessly connect and automate data flows between your systems and Azure Data Lake.

By leveraging Frends' task-based approach, you can configure and customize Azure Data Lake integrations according to your specific use cases. Frends has a variety of tasks for handling containers, directories and files on Azure Data Lake.

Getting Microsoft credentials

To get data needed for connection you need to register an application in Azure Active Directory and grant it the necessary permissions. Once you have registered the application, you can obtain the required credentials, which will be used to configure the connection in Frends. To do that you should do following steps:

1. Sign in to the Microsoft Entra admin center or Azure Portal.
2. Go to Identity > Applications > App registrations.
3. Select your application from the list (or create a New registration).
4. On the Overview page, copy the following values:

• Application (client) ID $\rightarrow$ ApplicationID
• Directory (tenant) ID $\rightarrow$ TenantID

1. The Client Secret acts as the "password" for the application. It is used to prove the application's identity when requesting a token.

Here you can find some useful Microsoft guides:

• How to find your Tenant ID
• Register an application with the Microsoft identity platform
• Create a new client secret

Use cases

Below you will find examples of typical use cases for Azure Data Lake and how they could be implemented in Frends.

Downloading files

By using the Schedule trigger in conjunction with the DownloadFiles task, we can create an integration that runs once every day and downloads files from an Azure Data Lake container that match a specified pattern.

Downloading files

Uploading files

By using the CreateContainer and UploadFiles tasks, we can create an integration that creates a container into Azure Data Lake, uploads files matching a pattern from a local folder into the Data Lake container, and deletes the local files afterwards.

Uploading files