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Data Engineering for Everyone

Discover how data engineers lay the groundwork that makes data science possible. No coding involved!

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2 Hours11 Videos32 Exercises98,024 Learners
2300 XP

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Course Description

In 2019, the average salary for data engineers overtook data scientists. How did this happen? Companies wanting to find the gold within their data realized it wasn’t possible if they hadn’t yet built the mine. Data engineers lay the foundations that make data science possible.

In this course, you’ll learn about a data engineer’s core responsibilities, how they differ from data scientists, and facilitate the flow of data through an organization. Through hands-on exercises you’ll follow Spotflix, a fictional music streaming company, to understand how their data engineers collect, clean, and catalog their data. By the end of the course, you’ll understand what your company's data engineers do, be ready to have a conversation with a data engineer, and have a solid foundation to start your own data engineer journey.

  1. 1

    What is data engineering?

    Free

    In this chapter, you’ll learn what data engineering is and why demand for them is increasing. You’ll then discover where data engineering sits in relation to the data science lifecycle, how data engineers differ from data scientists, and have an introduction to your first complete data pipeline.

    Play Chapter Now
    Data engineering and big data
    50 xp
    Go with the flow
    100 xp
    Not responsible
    100 xp
    Big time
    100 xp
    Data engineers vs. data scientists
    50 xp
    Tell me the truth
    50 xp
    Who is it
    100 xp
    The data pipeline
    50 xp
    It's not true
    50 xp
    Pipeline
    100 xp
  2. 2

    Storing data

    Free

    It’s time to talk about data storage—one of the main responsibilities for a data engineer. In this chapter, you’ll learn how data engineers manage different data structures, work in SQL—the programming language of choice for querying and storing data, and implement appropriate data storage solutions with data lakes and data warehouses.

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  3. 3

    Moving and processing data

    Free

    Data engineers make life easy for data scientists by preparing raw data for analysis using different processing techniques at different steps. These steps need to be combined to create pipelines, which is when automation comes into play. Finally, data engineers use parallel and cloud computing to keep pipelines flowing smoothly.

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In the following tracks

Data EngineerData Literacy Fundamentals

Datasets

Lexicon

Collaborators

Richie CottonLis Sulmont
Hadrien Lacroix Headshot

Hadrien Lacroix

Curriculum Manager at DataCamp

Hadrien has collaborated on 30+ courses ranging from machine learning to database administration through data engineering. He's currently enrolled in a Masters of Analytics at Georgia Tech.

Hadrien started using DataCamp when the platform only had 27 courses. He then joined the Support team and helped students before becoming a Content Developer himself.

Follow Hadrien on LinkedIn
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What do other learners have to say?

I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.

Devon Edwards Joseph
Lloyds Banking Group

DataCamp is the top resource I recommend for learning data science.

Louis Maiden
Harvard Business School

DataCamp is by far my favorite website to learn from.

Ronald Bowers
Decision Science Analytics, USAA