Vaibhav Pandey - Blogs - AWS Data Lake Requirements Process
Discovery workflow to uncover the core capabilities and controls behind an AWS data lake.
Quick takeaways:
- Maps the discovery workflow used to scope new AWS data lake engagements.
- Captures decision points such as streaming vs. batch ingestion, security controls, and integration touch points.
- Outputs actionable backlog items for implementation teams across governance, compliance, and analytics.
flowchart TD
A[1. Start] --> B{2. Understand Business Objectives}
B --> C[3. Identify Data Sources]
C --> D[4. Determine Data Volume and Velocity]
D --> E{5. Is Real-time Processing Needed?}
E -->|Yes| F[6. Plan for Streaming Data]
E -->|No| G[7. Plan for Batch Processing]
F --> H[8. Consider Data Processing Tools e.g., Kinesis, Lambda]
G --> I[9. Consider Data Processing Tools e.g., S3, Glue, EMR]
H --> J{10. Data Security Requirements?}
I --> J
J -->|Yes| K[11. Implement Security Measures e.g., Encryption, IAM]
J -->|No| L[12. Basic Security Measures]
K --> M[13. Choose Storage Solutions e.g., S3, Redshift]
L --> M
M --> N[14. Define Metadata Management Strategy]
N --> O[15. Plan for Data Governance and Compliance]
O --> P{16. Integration with Other AWS Services?}
P -->|Yes| Q[17. Identify Integration Points e.g., RDS, DynamoDB]
P -->|No| R[18. Proceed Without Additional Integrations]
Q --> S[19. End]
R --> S
This decision flow summarises the discovery questions used to scope an AWS data lake engagement, ensuring stakeholders agree on objectives, guardrails, and integrations before the platform build begins.