Building Incremental Data Pipelines Using Azure Data Factory

One of the most common and challenging problems in Data Engineering is how to efficiently and accurately detect changed data. In the cloud, relying on a full load pattern can be both time consuming and costly. In this session we will look at some common design patterns for detecting and loading new and updated data using Azure Data Factory. Along the way we will also explore some common techniques to make pipelines more dynamic and add additional auditing and logging.

Jason Horner

Global Thought Leader and International Man of Leisure

Denver, Colorado, United States


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