DP-203 Data Engineering on Microsoft Azure

Schedule data pipelines in Data Factory or Azure Synapse Pipelines

Troubleshoot a failed pipeline run, including activities executed in external services

Process within one partition

Troubleshoot a failed Spark job

Implement secure endpoints (private and public)

Configure error handling for a transformation

Process data across partitions

Tune queries by using cache

Encode and decode data

Implement a data retention policy

Process time series data

Shred JSON

Implement POSIX-like access control lists (ACLs) for Data Lake Storage Gen2

Tune queries by using indexers

Split data

Handle schema drift