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AWS Glue transforms and moves data seamlessly between data stores. Discover how to learn AWS Glue with edX and start solving real-world data integration challenges.

What is AWS Glue?

Organizations have data stored in various sources and in different formats. Preparing this data for analysis can take a lot of time if done manually. That’s where ETL (extract, transform, load) tools are useful. They help automate data extraction, transformation, and loading tasks and streamline the data preparation process.

AWS Glue is a fully-managed ETL tool that makes it easy for users to load data into data pipelines and data warehouses, like Amazon Redshift, and prepare data for analysis.1 Some of its key features and benefits include:

  • Compatibility with a wide range of data sources and targets

  • Automatic schema discovery that automatically determines the schema for your data and creates metadata in your AWS Glue Data Catalog

  • Easy scalability as and when the workload differs

Cost-effective pricing model (the AWS Glue price plans offer pay-as-you-go billing)

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AWS Glue tutorial curriculum

An AWS beginner-friendly course curriculum can provide an introduction to AWS Glue, including how to connect to data sources to manage your data and how to visually create and track ETL pipelines to load data into data lakes. You can learn about the AWS Glue Data Catalog, exploring how to populate the catalog with metadata tables and how to add connections to your data catalog.

More advanced courses may teach you how to:

  • Author and run data integration jobs

  • Use AWS Glue Studio to create AWS Glue jobs visually

  • Use and test scripts

  • Start crawlers with event-based triggers and automate workflows

To succeed in an AWS Glue course, it can help if you know about databases, data warehouses, and data models. Familiarity with Python and SQL can also help. A bachelor’s degree in a related field can provide a strong foundation. If you want a more comprehensive education, you can opt for a master’s degree.

For learners who want career-critical skills, an online executive education program can be a good fit for those with a busy schedule. Learners that want to acquire skills at a faster pace can opt for boot camps. Find the educational path that aligns with your needs and goals.

Explore AWS Glue jobs

AWS Glue can be useful in analytics, machine learning, and application development. Roles in which knowledge of AWS Glue can come in handy, include:

  • Data engineer: Designs and builds architectures that store and analyze data to support an organization’s data objectives.2

  • Big data developer: Creates and runs ETL tasks and scripts, moves data between various data sources, streamlines workflows, and increases productivity.3

  • Database administrators: Administers and implements databases and manages database management systems (DMS).4

  • Data scientist: Engages in ETL processes, clean ups and transforms data from various data sources, and prepares it for machine learning models.5

  • Data analyst: Collects, processes, and performs statistical analyses on data that help organizations make informed decisions and creates reports to communicate their observations.6

Each of these roles will have different education and skills requirements. For example, you may be able to build relevant skills in a data analytics boot camp. However, some employers may seek candidates with a degree in data science depending on the role. Before deciding on a specific learning path, research the positions you hope to pursue and align your coursework with your career goals.

[h3] How to use AWS Glue in your career

AWS Glue can be a valuable tool for professionals who want to advance in roles that involve ETL processes, big data, and data integrations. Once you have a solid grasp of AWS Glue, you can build machine learning models, create ETL scripts, and build data integration pipelines.

Some other work responsibilities of an ETL developer or architect include:

  • Creating and maintaining AWS Glue ETL jobs.

  • Developing and executing data conversions and migration scripts.

  • Configuring and handling the upkeep of AWS Glue crawlers to automate the data catalog process.

  • Troubleshooting data pipeline issues.

You may also need to work with various programming languages (like Python, Java, and Scala), big data technologies (like Apache Spark, NoSQL, and Spark databases), and other AWS Glue tools (like AWS Glue DataBrew, a visual data representation tool).

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    Frequently Asked Questions

    1. What Is AWS Glue? (2023). Amazon Web Services. Retrieved April 28, 2023.

    2. What Is a data engineer? An Analytics Role In High Demand. (2022). CIO. Retrieved April 28, 2023.

    3. Software Developers, Quality Assurance Analysts, and Testers. (2023). U.S. Bureau of Labor Statistics Occupational Handbook. Retrieved April 28, 2023.

    4. Database Administrators and Architects. (2022). U.S. Bureau of Labor Statistics. Retrieved April 28, 2023.

    5. Data Scientists. (2023). U.S. Bureau of Labor Statistics Occupational Handbook. Retrieved April 28, 2023.

    6. Data Analyst Job Description: Top Duties and Qualifications. (2023). Indeed. Retrieved April 28, 2023.