Mastering Analytical Data Lake : Amazon S3 Tables

New Advancement in Data Lake technology

What you'll learn

Design and implement scalable tabular data lakes using Amazon S3 Tables and Apache Iceberg.

Apply ACID transaction concepts to manage concurrent data operations in S3 Tables.

Integrate S3 Tables with AWS analytics services like Athena and Redshift for real-world workloads.

Optimize performance, security, and cost for tabular data storage and analytics on AWS.

Requirements

Basic understanding of AWS services is helpful but not required; all core concepts will be explained from scratch.

Description

Unlock the next generation of data lake analytics with Amazon S3 Tables. This comprehensive course is designed for data engineers, analysts, and cloud professionals seeking to master the new S3 Tables feature—distinct from standard Amazon S3 storage. Through hands-on demos, real-world scenarios, and practical integration guides, you’ll learn how S3 Tables enable high-performance, transactional analytics directly on your data lake, bridging the gap between object storage and modern analytics engines.What You’ll LearnFoundations of S3 Tables: Understand what Amazon S3 Tables are, how they differ from traditional S3 buckets, and why they matter for modern analytics workloads.Architecture & Operations: Dive into S3 Table bucket architecture, core components, APIs, and CLI operations for seamless table management.Transactional Data Lakes with Iceberg: Explore Apache Iceberg’s role in enabling ACID transactions, metadata management, and data compaction for reliable, scalable analytics.Hands-On CRUD with Athena: Practice creating, updating, and deleting S3 Tables using Amazon Athena, including namespace and table management.Lake Formation Integration: Learn how to secure and govern your S3 Tables with AWS Lake Formation, enabling enterprise-grade access controls and cataloging.Analytics Tool Integrations: Connect S3 Tables to AWS Glue, SageMaker Lakehouse, and Amazon QuickSight for powerful ETL, machine learning, and BI workflows.Streaming Data Pipelines: Ingest real-time data into S3 Tables using AWS Kinesis, unlocking up-to-date analytics on streaming datasets.Security, Pricing, and Best Practices: Master resource-based policies, understand pricing models, and apply scaling strategies for large-scale deployments.Who Should Take This Course?Data engineers, analysts, and architects familiar with AWS basics and looking to modernize their data lake architecturesCloud professionals and solution architects evaluating S3 Tables for analytics, governance, or streaming use casesAnyone seeking hands-on experience integrating S3 Tables with AWS’s analytics ecosystem

Overview

Section 1: Introduction to Amazon S3 Tables

Lecture 1 Introduction to Amazon S3 tables

Lecture 2 How is it different from Amazon S3 -General purpose storage?

Lecture 3 Iceberg- ACID, Metadata Management and Compaction

Section 2: S3 table administration

Lecture 4 Pre requisites for S3 Table access

Lecture 5 S3 Tables for Administrators

Section 3: S3 Table Buckets – Architecture and Concepts

Lecture 6 S3tables: Core Components & table Organization

Lecture 7 S3tables: APIs

Lecture 8 S3tables-CLI command for table operations

Section 4: Athena -Hand On S3 table CRUD Operations

Lecture 9 Create a S3 table Bucket

Lecture 10 Create a Namespace and Tables

Lecture 11 S3tables-INSERT,UPDATE,DELETE

Section 5: AWS LakeFormation and S3 Tables

Lecture 12 AWS LakeFormation-Integrate S3 tables

Lecture 13 AWS LakeFormation - Create an S3table

Section 6: Integrating S3 Tables with AWS analytical tools

Lecture 14 Integrating with Amazon SageMaker Lakehouse

Lecture 15 AWS Glue and S3 tables integration

Section 7: Streaming into S3tables

Lecture 16 S3 tables & Streaming

Lecture 17 Streaming data from AWS Kinesis to S3 tables

Section 8: QuickSight Integration with S3 tables

Lecture 18 Introduction to S3 Tables Integration with Quicksight

Lecture 19 Integrate S3 tables to Quicksight

Section 9: S3tables : Access Management,Pricing and Best practices

Lecture 20 S3tables: Resource based policies

Lecture 21 S3Tables : Pricing

Lecture 22 Scaling: quotas, limits, and best practices for large-scale deployments

Cloud engineers, data architects, analysts, and developers interested in building scalable, concurrent data lakes on AWS using S3 Tables and Iceberg.