Week 9 Worklog

Week 9 Objectives:

  • Get familiar with and practice Data & Analytics services on AWS.
  • Understand the data ingestion, storage, processing and analytics pipeline on the cloud.
  • Use AWS tools to build a Data Lake and create BI dashboards.

Tasks to be carried out this week:

DayTaskStart DateCompletion DateReference Material
2- Introduce the Data & Analytics ecosystem on AWS
- Understand Data Lake concepts, ETL pipelines, and how to connect data from multiple sources		03/11/202503/11/2025AWS Journey
3- Build a Data Lake on Amazon S3
- Design folder structure and access controls
- Configure AWS Glue Crawler to detect data schema		04/11/202504/11/2025AWS Journey
4- Practice querying the Data Lake with AWS Athena
- Write basic SQL queries and export results to S3		05/11/202505/11/2025AWS Journey
5- Introduction and hands-on with Amazon QuickSight
- Connect QuickSight to Athena for visualizations
- Create a simple dashboard with charts and summary tables		06/11/202506/11/2025AWS Journey
6- Review & consolidate the week:
+ Data ingestion → processing → analytics on AWS
+ Compare Glue, Athena, QuickSight with traditional tools
+ Write a summary report of exercises		07/11/202507/11/2025AWS Journey

Week 9 Achievements:

  • Understood how to build and manage a Data Lake using S3.

  • Practiced ingesting, cataloging and querying data with Glue and Athena.

  • Created a BI dashboard for visual analysis using QuickSight.