Data Engineering
Designing data architectures

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About the certificate course

Digitalization is creating an ever-increasing flood of data of all kinds in companies, which is required at various points in the business or production processes. The availability and usability of data is therefore essential for efficient corporate management. However, the diverse data management solutions that have emerged in recent years under the buzzword "Big Data" present companies with the challenge of deciding on suitable technologies.
In this certificate course, you will learn various aspects that are necessary for efficient and effective data management. In addition to the topics of data modeling (relational and NoSQL), data cleaning and data integration, the course also presents more comprehensive concepts for data architectures such as data warehouse, data lake or lambda architecture. Through practical exercises with current data management systems and the discussion of individual questions with the university teacher / lecturer, you will be able to transfer the contents of the course to your everyday work.

 

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Course objectives

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

  • Understand the application areas and limitations of classic relational database systems.
  • Explain and compare different architectures of data management systems.
  • Explain the data models of various NoSQL or Big Data systems and apply them for data modeling.
  • Implement data transformation processes for preparing and cleansing data.
  • Define data queries in various database systems.
Advantages
  • Increased knowledge and competence through the teaching of contemporary data architectures and data management methods from research and practice.
  • Independent and critical discussion and evaluation of current data management technologies.
  • Professional applicability of the content taught through practical orientation 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 respond to individual questions and problems posed by participants. Practical exercises on various data management systems based on case studies 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 Foundation course & data modeling

  • Foundation courses and terms
    Data, information; data modeling; database systems
  • Data modeling
    Process models for data analysis (CRISP-DM, Knowledge Discovery Pipeline) and the role of data engineering; relational and NoSQL database systems;
    Conceptual and logical data modeling;
    Exercises (reverse engineering of data models, data modeling with UML, data modeling procedure);
    Implementation of data models on the computer
  • Advantages and disadvantages of NoSQL and relational systems; role of data modeling in the company

II Data management

Data management architectures
Data warehouse and data lake; Lambda architecture and other approaches for the efficient processing of big data

Interaction with database systems

  • Definition of the necessary database structures
  • Structuring and importing data
  • Query languages, especially for SQL and NoSQL systems (e.g. MongoDB and Neo4j)

Comparison and evaluation of database systems

  • Criteria for evaluating database systems
  • Comparison and evaluation based on case studies

Assessment of database systems in the company
Project assignment for data modeling

III Data transformation

Data transformation
Data preparation, data cleaning, data integration
Introduction to data transformation tools
Practical exercises with data transformation tools (e.g. Talend, KNIME) on the computer; implementation of simple transformations for cleaning and integrating data from case studies
Presentation of project assignments and

  • Three online attendance dates:
    Mon., 03.06.2024 | Fri., 07.06.2024 | Fri., 21.06.2024 | 9 a.m. - 5 p.m.
    There are online-supported self-study phases between the attendance days.
  • Registration deadline: 24.05.2024
  • Number of participants: approx. 12 people
  • Location: Online format (Zoom meeting)
  • Course language: The certificate course is held in German.

 

  • Participation fee: 990 € | alumni (5% discount) 940 €
  • Participation requirements: University degree with at least one year of professional experience or other professionally qualifying degree with 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, if necessary, a headset.
  • Scope (workload): 75 h, of which attendance 24 h, 3 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 "Data Engineering" currently of interest to many professionals?
"Today, data is referred to as the "new oil" and is fundamental to many processes in companies. However, there is often a lack of adequate tools or methods for dealing with data, which means that the potential that lies in the data cannot be exploited. This continuing education course shows how data can be managed efficiently and effectively so that it can be used for more advanced applications."

What are you particularly looking forward to in this university certificate course?
"The discussions with the participants and the experiences they have had with data management in practical applications."

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