Data Engineering

Data extraction, transformation and aggregation but also enrichment and reduction are part of data engineering and they are all covered in this track.

Data, data, data,... it's everywhere and it is growing in volume, frequency and range and number of sources delivering it. The landscape is changing from on-premise to cloud and from 'stored' to in-memory or streaming. All of this is a lot to handle and so we have created a dedicated track to address all these topics. We cover extraction from flat files as well as different types of joins and aggregations in the first part but we also touch on big-data, data quality and cleansing and topics like text data processing along the way.

Sections

  • Professional

    Data Engineering Professional

    Elective
    Course
    Data Engineering is about all aspects of data and so is this course. We address how to access and load data, how to transform it and how to do calculations. Handling and joining multiple data tables is topic which is covered here as well as data types and how to convert them. Finally we address the basics of handling text data.
    Open

    Data Engineering Professional Certification

    Elective
    Certification Exam
    Take a quiz to verify your knowledge and understanding Data Engineering in RapidMiner
    Open

  • Master

    Data Engineering Master

    Elective
    Course
    This course is about advanced methods of handling, preparing and enriching data. It addresses data cleansing but also processing of unstructured text data. Commonly known methods like loops and branches are discussed but also the use of variables, error handling and different options to use scripting.
    Open

    Data Engineering Master Certification

    Elective
    Certification Exam
    Take a quiz to verify your knowledge and understanding Data Engineering in RapidMiner
    Open
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Learning Path Runs: Feb 11th 2022

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RapidMiner Academy Overview

We offer free access to micro-modular learning content through our Catalog.

The content is grouped into the general topics, 'Applications & Use Cases' 'Machine Learning', 'Data Engineering' and 'Administration and Deployment’. These topics form the basic structure for the majority of our Courses. They are designed with our users' role-based learning requirements in mind.

The same structure is also used for naming the Certification Exams which we provide to you for assessment and proof of your skills and to celebrate your learning progress.

For additional guidance, we have created Learning Paths.

Go to Catalog