AWS Glue is a serverless data integration service that helps you easily prepare and load data for analytics.
It offers powerful features like data crawling, job scheduling, and transformations, making it a valuable tool for data engineers and analysts.
By learning AWS Glue, you can unlock the potential of your data, automate ETL processes, and build data pipelines that connect diverse data sources to your analytics platform.
Finding a comprehensive and engaging AWS Glue course can be challenging, with numerous options available on Udemy.
You’re looking for a course that goes beyond theory, providing practical experience and hands-on projects to solidify your understanding.
You want a course that is taught by experienced instructors who can guide you through the intricacies of AWS Glue and equip you with the skills needed to confidently build and manage data pipelines in the real world.
Based on our thorough review, we highly recommend AWS Glue - The Complete Masterclass as the best overall course on Udemy for learning AWS Glue.
This course covers everything you need to know, from the fundamentals to advanced concepts, including hands-on exercises and real-world projects.
It’s also taught by experienced professionals with a deep understanding of AWS Glue and its applications.
This is just one of the many excellent AWS Glue courses available on Udemy.
Keep reading to explore our curated list of recommendations for different learning styles, experience levels, and specific use cases.
Whether you’re a beginner or an experienced data engineer, we have the perfect course to help you master AWS Glue and unlock the full potential of your data.
AWS Glue - The Complete Masterclass
You’ll start by mastering the fundamentals of AWS Glue, including managing user permissions with IAM, securing data with KMS, and setting up your development environment using the AWS CLI.
You’ll learn to leverage CloudFormation for streamlined resource creation and S3 for data storage, while gaining insights into monitoring your processes with CloudWatch.
The course takes a hands-on approach, guiding you through practical exercises.
You’ll delve into the intricacies of Glue Crawlers, learning how to extract data from diverse sources and build robust data pipelines.
You’ll master the art of creating Glue Jobs for data transformation and explore the powerful capabilities of Glue Pipelines to automate your ETL processes.
Along the way, you’ll gain expertise in using Glue Triggers and Workflows to orchestrate and schedule your jobs effectively.
You’ll further enhance your skills by creating CloudFormation Templates for efficient deployment and management of your AWS resources.
The course also addresses real-world challenges, guiding you through common debugging scenarios related to Glue Job scripts, resource access, and pipeline configuration.
The course delves into the world of Glue Streaming Jobs, empowering you to handle real-time data processing with ease.
You’ll also learn to implement robust data quality checks using AWS Glue, ensuring the accuracy and integrity of your data.
Finally, you’ll be introduced to Data Brew, a powerful tool for automated data preparation and profiling.
This section equips you with the knowledge to create data profiles, identify data quality issues, and build sophisticated data transformation recipes.
Data Lake, Firehose, Glue, Athena, S3 and AWS SDK for .NET
You’ll gain a strong understanding of core AWS services like S3, RDS, Kinesis Firehose, Glue, Athena, and Lake Formation.
The hands-on approach is a highlight, starting with practical exercises on setting up S3 buckets and RDS instances.
You’ll then dive into the powerful capabilities of Kinesis Firehose, learning how to use C# and the AWS SDK to build streaming data pipelines.
This section is particularly valuable as it equips you with the skills to efficiently ingest and process large volumes of data in real-time.
You’ll learn to leverage AWS Glue for data cataloging and schema definition, making your data readily accessible for analysis with Athena’s SQL query engine.
The course also covers ETL processes, demonstrating how to build automated workflows for data transformation and loading using Hangfire, a popular background processing framework.
Security and governance are emphasized through a thorough exploration of AWS Lake Formation and Cognito.
You’ll understand how to implement robust data access controls and user authentication mechanisms, crucial for safeguarding your data lake.
Finally, you’ll be introduced to Parquet, a columnar data format that can significantly boost query performance, offering a powerful alternative to Kinesis Firehose.
This course is ideal for developers and data engineers who want to build a solid foundation in AWS data lake architecture and best practices.
Learn Azure data factory and AWS GLUE (ETL)
You’ll learn to master the art of Extract, Transform, Load (ETL) processes, moving and transforming data from various sources to your desired destinations.
Get ready to dive deep into AWS Glue.
You’ll explore its architecture, understand key concepts like crawlers, jobs, and transformations, and even build a real-time project that utilizes AWS Glue with S3 and Lambda.
You’ll also discover the power of Athena, a query engine that lets you analyze data stored in S3.
Next, you’ll shift gears to ADF, a cloud-based ETL service within Azure.
Learn how to create data pipelines to move data between storage locations like S3 and Azure Blob Storage.
You’ll master techniques like copying and deleting data, transforming data using various operations such as union and filtering, implementing incremental loading, and leveraging parameterization.
The course also delves into different types of Slowly Changing Dimensions (SCD), a crucial technique for managing data changes in data warehouses.
To round out your learning experience, you’ll brush up on your SQL skills.
The course covers essential commands like CREATE, ALTER, DELETE, UPDATE, and JOIN, alongside important concepts like constraints and stored procedures.
You’ll even explore window functions like ROW_NUMBER, RANK, and DENSE_RANK, providing you with a solid understanding of data manipulation within relational databases.
This course provides a strong foundation in data engineering, equipping you with the skills to confidently manage and transform data across various platforms.
By mastering AWS Glue, ADF, and essential SQL concepts, you’ll be ready to tackle real-world data challenges.