Architecting Big Data Applications: Batch Mode Application Engineering

Introduction

• Welcome
• Platforms vs. applications
• Software architecture vs. design
• Notes on use cases

1. Intro to Big Data Applications

• Big data characteristics
• Traditional vs. big data applications
• Big data application modules
• Technologies for big data
• Strategy for big data apps

2. Use Case 1: Data Warehouse (DW)

• DW: Analyze the problem
• DW: Outline the solution
• DW: Consider technologies
• DW: Lay out the architecture
• DW: Design key elements
• Best practices: Data acquisition

3. Use Case 2: Log Accumulation (LA)

• LA: Analyze the problem
• LA: Outline the solution
• LA: Consider technologies
• LA: Lay out the architecture
• LA: Design key elements
• Best practices: Data transport

4. Use Case 3: IT Operations Analytics (OA)

• OA: Analyze the problem
• OA: Outline the solution
• OA: Consider technologies
• OA: Lay out the architecture
• OA: Design key elements
• Best practices: Data processing

5. Use Case 4: Customer 360 (C360)

• C360: Analyze the problem
• C360: Outline the solution
• C360: Consider technologies
• C360: Lay out the architecture
• C360: Design key elements
• Best practices: Data storage

6. Use Case 5: Customer Analytics (CA)

• CA: Analyze the problem
• CA: Outline the solution
• CA: Consider technologies
• CA: Lay out the architecture
• CA: Design key elements
• Best practices: Data service

Conclusion

• Next steps