Data Science on Google Cloud Platform: Architecting Solutions

Learn how to architect data science solutions at scale using the capabilities provided by Google Cloud Platform (GCP).

Introduction

• Architecting data science
• Use case (UC) notes

1. Architecting in GCP

• GCP benefits
• GCP shortcomings
• Enterprise: Cloud integration
• Multicloud integration

2. UC1: Cloud Data Archive

• UC1: Analyzing the problem
• UC1: Outlining the solution
• UC1: Considering technologies
• UC1: Laying out the architecture
• UC1: Designing key elements

3. UC2: Log Analytics

• UC2: Analyzing the problem
• UC2: Outlining the solution
• UC2: Considering technologies
• UC2: Laying out the architecture
• UC2: Designing key elements

4. UC3: Customer Analytics

• UC3: Analyzing the problem
• UC3: Outlining the solution
• UC3: Considering technologies
• UC3: Laying out the architecture
• UC3: Designing key elements

5. UC4: Real-Time Mobile Couponing

• UC4: Analyzing the problem
• UC4: Outlining the solution
• UC4: Considering technologies
• UC4: Laying out the architecture
• UC4: Designing key elements

Conclusion

• Next steps