Overview

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Explore modern data governance and analytics solutions on AWS, including Glue Data Catalog, Lake Formation, Athena, and Hive. Learn to manage metadata, enforce governance, and analyze data at scale using serverless and big data technologies. This course delves into AWS services that enable effective metadata management, data governance, and scalable analytics. Learners will understand how to use Glue Data Catalog for metadata repositories, implement fine-grained access control with Lake Formation, and leverage Athena and Hive for serverless and big data analytics. The course concludes with real-world project scenarios that integrate data modeling, Redshift, Athena, and Python for comprehensive analytics solutions. Learners engage with a combination of theoretical insights and practical demonstrations, focusing on integrating governance and analytics tools to build secure, scalable, and efficient data platforms. The course highlights best practices for managing metadata, enforcing governance, and optimizing analytics workflows on AWS. This course is part three of a three-course Specialization designed to build a complete and cohesive understanding of the subject. While it offers valuable skills on its own, you'll gain the most benefit by progressing through all three courses as a structured learning journey. This course is based on Data Engineering on AWS Vol 1 - OLAP & Data Warehouse, by Soumyadeep Dey. This course is licensed and distributed by Packt. All rights reserved. Packt is one of the world's most prolific publishers of cutting-edge technical content. For over two decades we've made it our mission to curate and publish the knowledge of only the very best technical experts. We focus on real-world courses that help our customers get the job done, with coverage that extends across a wide range of established and cutting-edge technical topics. If you're an individual or an organisation that embraces learning by doing, Packt is the perfect fit for you.

Syllabus

AWS Metadata Repository - Glue Data Catalog
- This module covers the fundamentals of AWS Glue Data Catalog, including metadata management, data store integration, and practical implementation using hands-on examples. Learners will gain a clear understanding of how to configure and use the Glue Catalog for various data sources like Aurora, Redshift, and S3.
Data Governance using AWS Lake Formation
- This module covers essential concepts and hands-on practices for implementing data governance using AWS Lake Formation. Learners will gain practical skills in setting up access controls, applying tag-based policies, and managing data filtering and cleanup processes. The module emphasizes real-world application through guided exercises and knowledge checks.
Data Lakehouse on AWS - Athena
- This module covers essential concepts and practical techniques for working with Amazon Athena in a data lakehouse environment. Learners will explore query execution, data formatting, performance tuning, and resource management strategies. The content emphasizes real-world application through hands-on exercises and theoretical insights.
Big Data Warehouse - Hive
- This module provides an in-depth understanding of big data warehousing with Hive, covering key topics such as Hadoop theory, data formats, Hive architecture, and hands-on practices for managing data. Learners will gain practical skills in working with Hive databases, tables, and partitioning techniques, as well as explore advanced concepts like ACID properties and materialized views.
PROJECTS - Redshift, Athena, DataModelling, Python
- This module provides hands-on experience with data modeling, Redshift SQL, Python coding, and performance tuning. Learners will explore real-world datasets and apply concepts to manage and optimize large-scale data systems. The content emphasizes practical skills in moving from OLTP to OLAP environments.

Taught by

Packt - Course Instructors

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