Validate your Data Engineering skills with 200 rigorous practice questions on Apache Spark, Delta Lake, and distributed
Sub Category
- Other IT & Software
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Objectives
- Optimize distributed data processing pipelines using Apache Spark, including managing shuffles, partitions, and broadcast joins.
- Architect scalable and reliable Data Lakes using Delta Lake, implementing ACID transactions and schema evolution.
- Resolve common Big Data performance bottlenecks, such as data skew (using salting techniques) and inefficient memory caching.
- Design high-throughput streaming and batch ingestion frameworks for IoT, financial, and enterprise audit data.
Pre Requisites
- A foundational understanding of Python or Scala, SQL, and general database concepts. Prior exposure to Big Data concepts (like cluster computing) is highly recommended.
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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