Linkedin Learning – Hands-On Introduction – Data Engineering
English | Tutorial | Size: 219.84 MB
In this course, instructor Vinoo Ganesh gives you an overview of the fundamental skills you need to become a data engineer. Learn how to solve complex data problems in a scalable, concrete way. Explore the core principles of the data engineer toolkit-including ELT, OLTP/OLAP, orchestration, DAGs, and more-as well as how to set up a local Apache Airflow deployment and full-scale data engineering ETL pipeline. Along the way, Vinoo helps you boost your technical skill set using real-world, hands-on scenarios.
Learning Objectives:
• Get an overview of the role and responsibilities of data engineering, including one of the primary tools in the data engineer’s toolkit, the data pipeline.
• Learn how orchestration fits into the data engineering and data pipeline ecosystem.
• Dive into the fundamental extract, transform, and load (ETL) pattern and how it applies to Airflow.
• Review three frequently used concepts in the data engineering and Airflow world: tasks, DAGs (Directed Acyclic Graphs), and dependencies.
• Take a high-level look at Airflow and how it empowers data engineers to create automated workflows.
• Walk through how to install and run Airflow and modify configuration settings of an Airflow environment.
• Apply manual operations to extract, transform, and load data.
• Author basic extract, transform, and load operations using Airflow tasks and build a complete ETL DAG in Airflow using extract, transfer, and load tasks.
• Review other key topics, such as data governance and security, cloud deployment and adoption, real-time data, cross-team collaboration, AI and machine learning.
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