*Continue studying and practicing lab of module 7
| Day | Task | Start Date | Completion Date | Reference Material |
|---|---|---|---|---|
| 2 | - Data Lake on AWS - Practice: + Creating an IAM Role + Create Policy + Create S3 Bucket + Creating a Delivery Stream + Create Sample Data + Create Glue Crawler + Data Check + Create SageMaker Notebook + Analysis with Athena + Visualize with QuickSight + Clean up resources | 11/03/2025 | 11/03/2025 | https://000035.awsstudygroup.com/ |
| 3 | - LHOL: Hands-on Labs for Amazon DynamoDB - Practice: + Getting Started + Explore DynamoDB with the CLI + Explore the DynamoDB Console + Backups + LMIG: Relational Modeling & Migration - LBED: Generative AI with DynamoDB zero-ETL to OpenSearch integration and Amazon Bedrock - Practice: + Getting Started + Service Configuration + Integrations + Query and Conclusion | 11/04/2025 | 11/04/2025 | https://000039.awsstudygroup.com/ |
| 4 | - LADV: Advanced Design Patterns for Amazon DynamoDB - Practice: + Getting Started + Exercise 1: DynamoDB Capacity Units and Partitioning + Exercise 2: Sequential and Parallel Table Scans + Exercise 3: Global Secondary Index Write Sharding + Exercise 4: Global Secondary Index Key Overloading | 11/05/2025 | 11/05/2025 | https://000039.awsstudygroup.com/ |
| 5 | - LADV: Advanced Design Patterns for Amazon DynamoDB - Practice: + Exercise 5: Sparse Global Secondary Indexes + Exercise 6: Composite Keys + Exercise 7: Adjacency Lists + Exercise 8: Amazon DynamoDB Streams and AWS Lambda | 11/06/2025 | 11/06/2025 | https://000039.awsstudygroup.com/ |
| 6 | - LCDC: Change Data Capture for Amazon DynamoDB - Practice: + Getting Started + Scenario Overview + Change Data Capture using DynamoDB Streams Change Data + Capture using Kinesis Data Streams + Summary and Clean Up | 11/07/2025 | 11/07/2025 | https://000039.awsstudygroup.com/ |
Built a complete Data Lake on AWS, including S3 storage, Glue cataloging, Kinesis delivery streams, Athena queries, SageMaker notebooks, and QuickSight visualizations.
Strengthened NoSQL skills through hands-on DynamoDB labs, exploring CLI operations, backups, relational modeling patterns, and zero-ETL integrations with OpenSearch and Amazon Bedrock.
Learned and applied advanced DynamoDB design patterns, including capacity planning, partitioning, parallel scans, write sharding, sparse indexes, composite keys, adjacency lists, and stream processing.
Implemented Change Data Capture (CDC) workflows for DynamoDB using both DynamoDB Streams and Kinesis Data Streams.
Gained strong practical experience in data engineering, NoSQL data modeling, real-time data processing, and analytics on AWS.