The Unstructured Data Store compound pattern represents a solution environment capable of ingesting large amounts of semi-structured and unstructured data in order to perform predictive and prescriptive analytics by creating high-fidelity statistical and machine learning models.

Required (Core)

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

Optional (Extension)

• Relational Sink
• File-based Sink
• Data Size Reduction
• File-based Source
• Processing Abstraction
• Direct Data Access

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.