A end-to-end data pipeline using AWS services (S3, Glue, Redshift, EventBridge, SNS, QuickSight) for movie data analysis, ensuring automated ingestion, transformation, quality assurance, and insightful visualizations.
Movie Data Analysis with AWS
Project Overview
This project demonstrates a comprehensive data engineering pipeline for analyzing movie data using various AWS services. It highlights automated data ingestion, transformation, quality assurance, and visualization to derive actionable insights from movie datasets.
Tech Stack
⦿ Amazon S3: Centralized storage for raw movie data files.
⦿ AWS Glue Data Catalog: Manages metadata and provides a unified data view.
⦿ AWS Glue (Low Code ETL): Facilitates data transformation with minimal coding.
⦿ Glue Crawler: Automates schema discovery and data classification.
⦿ Glue Data Quality: Ensures data accuracy, completeness, and consistency.
⦿ Amazon Redshift: Data warehousing solution for efficient querying and analytics.
⦿ Amazon EventBridge: Manages event-driven processing and workflows.
⦿ Amazon SNS: Sends notifications for pipeline statuses and alerts.
⦿ Amazon QuickSight: Provides interactive dashboards and data visualizations.
The project involves:
⦿ Data Ingestion: Movie data files are uploaded to Amazon S3.
⦿ Schema Discovery: AWS Glue Crawlers automatically discover and catalog the data schema.
⦿ Data Transformation: Using AWS Glue’s low-code ETL capabilities, data is transformed, cleansed, and loaded into Amazon Redshift.
⦿ Data Quality Checks: Implementing Glue Data Quality to ensure the data meets predefined quality standards.
⦿ Data Warehousing: Transformed data is stored in Amazon Redshift, enabling efficient querying.
⦿ Event Management: Amazon EventBridge orchestrates the workflow, triggering processes based on data events.
⦿ Notifications: Amazon SNS sends notifications regarding pipeline status, ensuring proactive monitoring.
⦿ Visualization: Amazon QuickSight provides interactive and insightful visualizations of the processed data.
This project showcases the effective use of AWS services to build a robust, scalable, and automated data pipeline for movie data analysis, ensuring high data quality and providing meaningful insights through powerful visualizations. This experience demonstrates proficiency in modern data engineering practices and AWS technologies, making it a valuable addition to any data-driven organization.