Chapter 1

Section 1: Designing Data Processing Systems

• Storage technology selection
• Data pipeline design
• Data processing solution design
• Data Warehousing & Processing Migration

Section 2: Building & Operationalizing Data Processing Systems

• Storage system implementation
• Pipeline Building & Operationalization
• Processing infrastructure implementation

Section 3: Operationalizing ML Models

• Pre-built ML models as a service
• ML pipeline deployment
• Training & serving infrastructure selection
• ML model measurement, monitoring & troubleshooting

Section 4: Ensuring Solution Quality

• Security & compliance design
• Scalability & efficiency assurance
• Reliability & fidelity assurance
• Flexibility & portability assurance