The Batch Data Processing compound pattern represents a solution environment capable of ingesting large amounts of structured data for the sole purpose of offloading existing enterprise systems from having to process this data.

Required (Core)

• Relational Source
• Relational Sink
• Streaming Access Storage
• Automatic Data Replication and Reconstruction
• Automated Dataset Execution
• Large-Scale Batch Processing

Optional (Extension)

• Complex Logic Decomposition
• Confidential Data Storage
• Dataset Denormalization

This pattern is covered in BDSCP Module 10: Fundamental Big Data Architecture.

For more information regarding the Big Data Science Certified Professional (BDSCP) curriculum,
visit www.arcitura.com/bdscp.