Sifflet
Data observability platform for data quality monitoring and lineage; the API returns monitors, incidents, assets and lineage.
- Category
- Cloud & Data Platforms
- Type
- Data observability
- Interface
- REST API
- Built with
- Connect Any API
- Credentials
- Access token
- Docs
- Sifflet API docs
02Data
What you can sync.
- Monitors
- Incidents
- Assets
- Lineage
- Monitor runs
Load Sifflet monitors into your Lake and model it in the Warehouse with the rest of your stack.
Need more? Name any other Sifflet data the API returns, and the AI adds it to the connector.
03Credentials
Credentials you will need.
- An access token
Sifflet uses an access token. You add the credentials once, when the AI asks for them, and it tells you where to create them in Sifflet if you need help.
04How it works
How it works in DataMind.
-
Pick Sifflet.
Open Lake, pick Sifflet in the source picker and name the connection. Connect Any API opens with a ready prompt that points the AI at the Sifflet API docs.
-
Answer a few questions.
The AI reads the Sifflet documentation, then asks which credentials you will use, which data to sync (for example monitors and incidents), 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 Sifflet data loads into your Lake on your schedule, ready for the Warehouse, DataPrism BI and AI Minds.
