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Introduction to Data Engineering

Learn about the world of data engineering with an overview of all its relevant topics and tools!

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4 Hours15 Videos57 Exercises81,582 Learners4100 XPData Engineer Track

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Course Description

Have you heard people talk about data engineers and wonder what it is they do? Do you know what data engineers do but you're not sure how to become one yourself? This course is the perfect introduction. It touches upon all things you need to know to streamline your data processing. This introductory course will give you enough context to start exploring the world of data engineering. It's perfect for people who work at a company with several data sources and don't have a clear idea of how to use all those data sources in a scalable way. Be the first one to introduce these techniques to your company and become the company star employee.

  1. 1

    Introduction to Data Engineering

    Free

    In this first chapter, you will be exposed to the world of data engineering! Explore the differences between a data engineer and a data scientist, get an overview of the various tools data engineers use and expand your understanding of how cloud technology plays a role in data engineering.

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    What is data engineering?
    50 xp
    Tasks of the data engineer
    50 xp
    Data engineer or data scientist?
    100 xp
    Data engineering problems
    50 xp
    Tools of the data engineer
    50 xp
    Kinds of databases
    50 xp
    Processing tasks
    50 xp
    Scheduling tools
    50 xp
    Cloud providers
    50 xp
    Why cloud computing?
    50 xp
    Big players in cloud computing
    100 xp
    Cloud services
    100 xp
  2. 2

    Data engineering toolbox

    Now that you know the primary differences between a data engineer and a data scientist, get ready to explore the data engineer's toolbox! Learn in detail about different types of databases data engineers use, how parallel computing is a cornerstone of the data engineer's toolkit, and how to schedule data processing jobs using scheduling frameworks.

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  3. 3

    Extract, Transform and Load (ETL)

    Having been exposed to the toolbox of data engineers, it's now time to jump into the bread and butter of a data engineer's workflow! With ETL, you will learn how to extract raw data from various sources, transform this raw data into actionable insights, and load it into relevant databases ready for consumption!

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  4. 4

    Case Study: DataCamp

    Cap off all that you've learned in the previous three chapters by completing a real-world data engineering use case from DataCamp! You will perform and schedule an ETL process that transforms raw course rating data, into actionable course recommendations for DataCamp students!

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In the following tracks

Data Engineer

Collaborators

AAN94
Adel Nehme
Vincent Vankrunkelsven Headshot

Vincent Vankrunkelsven

Data and Software Engineer @DataCamp

Vincent has a Master's degree in Computer Science and has several years of experience scaling up the DataCamp's platform as a Software Engineer. He experienced first-hand the difficulties that come with building scalable data products. This made him passionate about teaching people how to do tackle these problems the right way.
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