AWS for Data Science: Mastering Data Storage & Querying with S3, Athena, RDS & Redshift (V2/4)

This comprehensive video lecture series guides data scientists through the essential AWS services for managing and querying large-scale datasets. We begin by exploring the fundamentals of data management on AWS, covering a range of storage and database solutions. You'll get a deep dive into Amazon S3, learning how to organize data with folders, manage object versions, and optimize costs with lifecycle policies.

Next, we'll demonstrate how to query data directly from S3 using Amazon Athena and standard SQL, eliminating the need for complex ETL pipelines. We'll also cover the role of AWS Glue for schema management and data cataloging. The series then shifts to structured data, where we explore the use cases for Amazon RDS for transactional workloads (OLTP) and Amazon Redshift for analytical processing (OLAP).

The lecture includes hands-on demonstrations where we store a CSV file in S3, query it with Athena, and load it into a pandas DataFrame. By the end of this series, you will have the knowledge to effectively manage and analyze datasets at scale in the AWS cloud.

Chapters:
0:00 - Introduction to the Video
1:08 - Managing Data on AWS: Storage and Databases
5:51 - Understanding Storage Types: Object vs. File vs. Block
12:30 - Introduction to Databases on AWS
19:55 - Deep Dive into S3 for Data Science Workflows
23:05 - Exploring S3 Bucket Types
27:34 - Organizing Data with S3 Folders (Prefixes)
30:04 - Managing S3 Objects and Lifecycle Policies
38:00 - S3 Bucket Versioning Explained
43:53 - Managing Bucket Policies and Public Access
57:05 - Creating S3 Lifecycle Rules in Detail
1:01:46 - Querying Data Directly with Athena SQL on S3
1:05:27 - Hands-On Demo: Querying CSV Data in S3 with Athena
1:22:21 - Automating Schema Creation with AWS Glue Crawlers
1:36:43 - Programmatically Generating Athena Table Schemas with Python
1:49:03 - Using RDS and Redshift for Structured Data
1:52:34 - Hands-On Demo: Creating and Connecting to an Amazon RDS Instance
2:09:51 - Hands-On Demo: Loading Data from S3 into Amazon Redshift