Apache Spark Essential Training: Big Data Engineering
With Kumaran Ponnambalam
Liked by 673 users
Duration: 1h 2m
Skill level: Advanced
Released: 9/15/2021
Course details
Data engineering is the foundation for building analytics and data science applications in the new Big Data world. Data engineering requires combining multiple big data technologies to construct data pipelines and networks to stream, process, and store data. This course focuses on building full-fledged solutions that combine Apache Spark with other Big Data tools to create end-to-end data pipelines. Instructor Kumaran Ponnambalam begins by defining data engineering, its functions, and its concepts. Next, Kumaran goes over how Spark capabilities such as parallel processing, execution plans, state management options, and machine learning work with extract, transform, load (ETL). He introduces you to batch processing use cases and processes, as well as real-time processing pipelines. After walking you through several useful best practices, Kumaran concludes with an end-to-end exercise project.
Skills you’ll gain
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Share what you’ve learned, and be a standout professional in your desired industry with a certificate showcasing your knowledge gained from the course.
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Certificate of Completion
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Showcase on your LinkedIn profile under “Licenses and Certificate” section
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Meet the instructor
Learner reviews
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Anjalipriya Rajulagari
Anjalipriya Rajulagari
Graduate Student at University of New Haven | Actively lokking for internships in Data Engineer role
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Esteban Mendez
Esteban Mendez
Data Quality Engineer | Data Analyst | Full-Stack Software Developer
Contents
What’s included
- Practice while you learn 1 exercise file
- Test your knowledge 3 quizzes
- Learn on the go Access on tablet and phone