Analytics & Reporting System MVP
A minimal viable reporting solution on AWS, focusing on the business application and data publishing, while deferring the full Analytics & Reporting system implementation.
Let me explain this minimal viable reporting approach:
Business Application:
A. Application Layer
API Gateway + Lambda for APIs
Serverless architecture for scalability
Event-driven design
B. Data Storage
DynamoDB for transactional data
Use DynamoDB Streams for change capture
Enable point-in-time recovery
C. Event Publishing
EventBridge for event routing
SNS for notifications
SQS for decoupling
Data Capture Layer:
A. Streaming Layer
Kinesis Data Streams for real-time data
Kinesis Firehose for S3 delivery
Configure retry policies
B. Raw Storage
S3 buckets with lifecycle policies
Organize by date partitions
Enable versioning
C. Basic Processing
AWS Glue for simple ETL
Lambda for light transformations
Maintain data formats
Quick Reporting Solutions:
A. Athena Queries
Direct SQL access to S3 data
Create views for common queries
Optimize for cost
B. QuickSight
Basic dashboards
Scheduled reports
Share with stakeholders
C. Basic APIs
Simple query endpoints
Data export APIs
Basic authentication
Implementation Steps:
Initial Setup:
- Create S3 buckets
- Configure Kinesis
- Set up IAM roles
- Enable monitoring
Data Flow:
- Configure DynamoDB streams
- Set up Kinesis Firehose delivery
- Create basic Glue jobs
- Enable Athena
Basic Reports:
- Create Athena tables
- Build QuickSight dashboards
- Implement basic APIs
- Set up monitoring
Security Controls:
- IAM policies
- Encryption at rest
- Encryption in transit
- Access logging
Key Benefits:
Minimal initial investment
Scalable architecture
Pay-per-use pricing
Easy to extend later
This approach allows you to:
Start capturing all necessary data
Provide basic reporting capabilities
Scale as needed
Migrate to full analytics later
Would you like me to elaborate on any specific component or provide more implementation details?
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