2. 2.1. Introduction
3. 2.2. Hyperscalable Systems
4. 2.3. Principles of Hyperscalable Systems
5. 2.4. Related Work
6. 2.5. Conclusions
7. References
2. Chapter 3: Architecting to Deliver Value From a Big Data and
Hybrid Cloud Architecture
1. Abstract
2. 3.1. Introduction
3. 3.2. Supporting the Analytics Lifecycle
4. 3.3. The Role of Data Lakes
5. 3.4. Key Design Features That Make a Data Lake Successful
6. 3.5. Architecture Example – Context Management in the IoT
7. 3.6. Big Data Origins and Characteristics
8. 3.7. The Systems That Capture and Process Big Data
9. 3.8. Operating Across Organizational Silos
10. 3.9. Architecture Example – Local Processing of Big Data
11. 3.10. Architecture Example – Creating a Multichannel View
12. 3.11. Application Independent Data
13. 3.12. Metadata and Governance
14. 3.13. Conclusions
15. 3.14. Outlook and Future Directions
16. References
3. Chapter 4: Domain-Driven Design of Big Data Systems Based on a
Reference Architecture
1. Abstract
2. 4.1. Introduction
3. 4.2. Domain-Driven Design Approach
4. 4.3. Related Work
5. 4.4. Feature Model of Big Data Systems
6. 4.5. Deriving the Application Architectures and Example
7. 4.6. Conclusion
8. References
4. Chapter 5: An Architectural Model-Based Approach to Quality-
Aware DevOps in Cloud Applicationsc
1. Abstract
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