Course

Parallel Processing for Data Engineering

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Part of the Data Engineer path.

4.8 (359 reviews)
1,780 learners enrolled in this course.
  • Advanced friendly
  • 5 hours
  • Self paced
  • 5 lessons
  • 1 project
Otavio

“The learning paths on Dataquest are incredible. They give you a direction through the learning process – you don’t have to guess what to learn next.”

Otávio Silveira

Data Analyst @ Hortifruti

Parallel Processing for Data Engineering

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Course overview

Key skills

Course outline

Parallel Processing for Data Engineering [5 lessons]

Introductions to Parallel Processing 1h

Lesson Objectives
  • Start multiple processes
  • Run functions on several processes at the same time
  • Share data between multiple processes

Process Pool Executors 1h

Lesson Objectives
  • Gather the results of a function executed on several processes
  • Employ a process pool executor
  • Analyze the demand for data engineering skills in job postings

Introduction to MapReduce 1h

Lesson Objectives
  • Define the MapReduce framework
  • Employ process pools
  • Implement MapReduce

Processing Data with MapReduce 1h

Lesson Objectives
  • Employ the MapReduce framework
  • Analyze words in English

Guided Project: Analyzing Wikipedia Pages 1h

Lesson Objectives
  • Analyze Wikipedia pages using MapReduce computing

Projects in this course

Guided Project: Analyzing Wikipedia Pages

Use MapReduce to analyze Wikipedia pages more quickly.

View Project

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Challenge yourself with exercises

Challenge yourself with exercises

Work with real data from day one with interactive lessons and hands-on exercises.

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Showcase your path certification

Impress employers by completing a capstone project and certifying it with an expert review.

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