This project aims to build an ETL (Extract, Transform, Load) pipeline using Python and various AWS tools and services. The pipeline processes a YouTube video dataset, performing data analytics and transformation tasks.

Languages: SQL, Python 3 Services: AWS S3, AWS Glue, QuickSight, AWS Lambda, AWS Athena, AWS IAM

A data pipeline is established to transfer raw data from various sources to destinations. It includes processes such as data collection, storage, analytics, and transformation to prepare data for querying.

Amazon S3 provides highly scalable and durable object storage for various data types. It offers high availability, scalability, and cost-effective storage options.

AWS Identity and Access Management enables secure management of access and permissions to AWS resources. It allows defining fine-grained access controls to ensure security and compliance within the AWS infrastructure.

Amazon QuickSight is a serverless business intelligence service that offers scalable analytics capabilities. It connects to various data sources and provides cost-effective BI solutions.

AWS Glue is a serverless data integration service that simplifies data preparation and integration tasks. It supports running Spark/Python code without managing infrastructure, making it cost-effective and efficient.

AWS Lambda is a serverless computing service that executes code without managing servers. It automates infrastructure management, scaling, monitoring, and logging, making it ideal for running data processing tasks.

AWS Athena is a serverless query service for analyzing data stored in Amazon S3 using SQL queries. It offers on-demand scalability and cost-effectiveness for ad-hoc data analysis tasks.

1. Data Collection: Upload the YouTube dataset to AWS S3.
2. Data Processing: Utilize AWS Glue for data preparation and transformation.
3. Querying Data: Use AWS Athena to analyze the transformed data with SQL queries.
4. Visualization: Visualize insights using QuickSight dashboards.
5. Automation: Implement automation using AWS Lambda for scheduled or event-triggered tasks.