Big data technologies
Developing scalable, distributed big data systems

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About the certificate course

To cope with the increasing flood of information, many technologies have been brought onto the market in recent years under the buzzword "big data" in order to develop efficient, scalable applications that can process large volumes of data. However, the range of commercial and free open source software is so large that even experts find it difficult to select suitable technologies for a particular application.


In this certificate course, you will gain an overview of various big data systems (e.g. Hadoop, Spark) and learn which use cases they are suitable for through practical case studies. In addition, you will learn the basic principles of distributed, scalable big data architectures in order to be able to classify and evaluate systems accordingly. Through practical exercises with current big data systems and the discussion of individual questions, you will be able to transfer the content of the course to your everyday work.

 

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Course objectives

Upon successful completion of the course, you will be able to

  • Explain and compare different architectures of Big Data systems.
  • Evaluate the advantages and disadvantages of distributed Big Data systems and justify their use.
  • Implement data transformations and data queries in Big Data systems.
  • Design and develop simple Big Data systems for specific requirements.
  • Evaluate own or existing Big Data systems.
Advantages
  • Increased knowledge and competence through the communication of contemporary big data architectures
    and systems from research and practical application.
  • Independent and critical discussion and evaluation of current big data technologies.
  • Professional applicability of the content taught through practical exercises and project assignments.
Target group

The certificate course is aimed at specialists and managers from all sectors in the fields of information management, organization and process management,...

  • who are responsible for the strategic planning of information architectures in a company.
  • who define information systems and processes in companies and coordinate their use.
Form of teaching and learning

The interactive seminar-style course offers the opportunity to address individual questions and problems posed by participants. Practical implementation tasks for big data systems with various case studies and data sets as well as support through an online learning platform support the learning success. The content learned is applied and advanced in practice as part of a project assignment.

I Scalable big data architectures

Fundamentals and Concepts
Distributed Data Management Systems
Scalable Architectures, Apache Hadoop and Apache Spark
Big Data Architectures
- Vertical and Horizontal Scalability
- Foundation Courses of Distributed Systems
- Cloud Computing
- Lambda and Kappa Architecture for Big Data
Big Data System: Hadoop
- Architecture Hadoop
- Distributed Processing with Map-Reduce
- Implementation of Data Processing Processes
Big Data System: Apache Spark
- ComparisonHadoop and Spark
- Architecture Apache Spark
- Introduction to programming simple data processing and analysis processes
Exercises on Hadoop, Spark and related technologies using practical examples
Project assignment on data processing and analysis with Apache Spark orHadoop based on case studies or own use cases from the company

II Data management

Exercises on Apache Spark with practical examples
Role of Apache Spark in distributed Big Data architectures
Current trends in Big Data systems
Presentation of project assignments and discussion

  • Two online attendance dates:
    Fr., 06.09.2024 | Fr., 20.09.2024 | each 9 a.m. - 5 p.m.
    There are online-supported self-study phases between the attendance days.
  • Registration deadline: 29.08.2024
  • Max. Number of participants: 12 persons
  • Location: Online format (Zoom meeting)
  • Course language: The certificate course is held in German.
  • Participation fee: 595 € | alumni (5% discount) 565 €
  • Participation requirements: University degree with one year of professional experience or vocational training and at least three years of professional experience. You should have basic knowledge of data architectures. You will need an internet-enabled PC or an internet-enabled notebook for Zoom as a video conferencing service and a headset if necessary.
  • Scope (workload): 50 h, of which attendance 16 h, 2 ECTS
  • Degree: University certificate / certificate of attendance
    Participants receive a certificate of attendance if at least 75% of the course is attended. A certificate from The Hochschule Niederrhein is awarded upon passing the examination.
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Three questions for your university teacher / lecturer, Prof. Dr. Quix:

Why is continuing education in "Big Data technologies" currently of interest to many professionals?
"Many technologies have been developed in recent years under the banner of "big data", making it difficult even for experts to maintain an overview. The continuing education course gives participants the opportunity to gain an insight and overview of current big data technologies and get to know them through practical exercises and case studies within the course."

What are you particularly looking forward to on this university certificate course?
"The discussion with the participants and the experiences they have had with big data technologies in practical application."

And what can participants look forward to?
"A practical and interactive continuing education course with lots of practical exercises."

Your contact person:

Ulrike Schoppmeyer
Center for continuing education Marketing | Sales