Azure Data Factory
by Microsoft
Azure cloud ETL and data integration service; its REST API exposes pipelines, pipeline runs, activity runs and triggers.
- Category
- Cloud & Data Platforms
- Type
- Data integration
- Interface
- REST API
- Built with
- Connect Any API
- Credentials
- OAuth 2.0, Service account key
02Data
What you can sync.
- Pipelines
- Pipeline runs
- Activity runs
- Triggers
- Datasets
Load Azure Data Factory pipelines into your Lake and model it in the Warehouse with the rest of your stack.
Need more? Name any other Azure Data Factory data the API returns, and the AI adds it to the connector.
03Credentials
Credentials you will need.
- OAuth 2.0 (client ID, client secret, refresh token)
- A service account key
Azure Data Factory uses OAuth 2.0 (client ID, client secret, refresh token) or a service account key. You add the credentials once, when the AI asks for them, and it tells you where to create them in Microsoft if you need help.
04How it works
How it works in DataMind.
-
Pick Azure Data Factory.
Open Lake, pick Azure Data Factory in the source picker and name the connection. Connect Any API opens with a ready prompt that points the AI at the Azure Data Factory API docs.
-
Answer a few questions.
The AI reads the Azure Data Factory documentation, then asks which credentials you will use, which data to sync (for example pipelines and pipeline runs), whether you want a one-time load or a recurring sync, and which accounts or filters apply.
-
Your data lands in Lake.
It builds the connector, tests it and shows you sample rows. Then Azure Data Factory data loads into your Lake on your schedule, ready for the Warehouse, DataPrism BI and AI Minds.
