| Term | Short interview explanation |
|---|---|
| Azure Data Factory (ADF) | Cloud service for data ingestion, movement, and pipeline orchestration. |
| Linked Service | Connection information for a source or destination, such as Azure SQL or Blob Storage. |
| Dataset | Represents the data structure/location that an ADF activity reads or writes. |
| Pipeline | A collection of activities that performs a data workflow. |
| Activity | An individual task inside a pipeline, such as Copy Activity or executing a notebook. |
| Trigger | Starts a pipeline based on a schedule or event. |
| Integration Runtime | The compute/connectivity infrastructure ADF uses to move data or execute activities. |
| Parameterization | Making pipelines dynamic and reusable by passing values instead of hard-coding them. |
| Metadata-driven pipeline | One generic pipeline uses configuration/metadata to process many tables or sources. |
| Incremental Load | Loading only new or changed records instead of the entire dataset. |
| Watermark | A stored value such as LastModifiedDate used to identify new/changed records. |
| CDC | Change Data Capture tracks inserts, updates and deletes from a source system. |