Master Airflow, Spark, and Data Lakes to build & deploy robust ETL pipelines on AWS & GCP Cloud.
Sub Category
- Other IT & Software
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Objectives
- Design, implement, and optimize end-to-end ETL/ELT data pipelines using modern engineering principles and best practices.
- Master Apache Airflow for scheduling, monitoring, and managing complex Directed Acyclic Graphs (DAGs) in a production setting.
- Utilize Python and SQL effectively for data extraction, cleansing, transformation, and loading operations.
- Implement distributed processing using Apache Spark (PySpark) to handle large-scale, massive datasets efficiently.
Pre Requisites
- Foundational knowledge of Python programming (loops, functions, and basic data structures).
- Basic proficiency in SQL and familiarity with relational database concepts.
- Access to a computer capable of running cloud environments and local development tools.
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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