Kies op maat

Inloggen Menu

(Big) Data Engineering

Do you ever wonder how companies get all this information about you? And how reliable this information is and what can be done with data? Are you not afraid to dive deep in to the data matter with several experts? Then the Data Engineering minor is for you.

You will research which data models can be used and how to use them. You will explore the ethical, technical and business issues of data. You will discover how to creatively and robustly apply Data Engineering while purpose and target groups of your products will be key.

Next to extensive participation of organisations, theories will be presented about the workings of data transformation techniques and you have the opportunity to use the latest technologies next to working on your research skills. Every week a guru in the field will provide a workshop because the world of digital development and users doesn’t stop. We zoom in on issues that will connect with your previous knowledge and interests and will fit with the project your group chooses. With current cases we will provide a motivating enrichment of your study and possibly the start of a promising career in the data field.

Examples of projects are:

• Create a data backbone for the cmi data lab. • Help predict sand dunes and growth of dunes to protect the country from flooding . • Help the ACED project to create a sustainable and robust data architecture to keep track of all Dutch media. • Help improve the data backbone and add data features for Ed Tech With AI. • Assist with the 3D city model for Rotterdam development to better serve the public. • Work on the data side of the Care4Tech project, using data to improve healthcare (privacy issues, taxonomies, NLP, etc). Projects are different every semester.
Content and program

OP3:
Group assignments
  • Data quality research
  • Project data value chain part 1
Individuel assignment
explore actual DE topic

OP4
Group assignments
  • Data quality product 
  • Project data value chain part 2 
    --> Project carrousel and product

Individuel assignment
Create innovative DE solutions
--> Research carrousel and portfolio

Theory
The theoretical part consists of lectures / tutorials and workshops. The theory creates a framework for looking at the challenges in practice and offers practical tools / skills to get started.

Practice
During the practical part, you and your group will realize an entire data value chain for an organization. Of course, the interests and challenges per organization are very different and it is up to you to create the best solution for this.

This practice will help you to connect the theories into context.

Teaching programmes
Lectures/ seminars, workshops, meetups and company visits.

Leerdoelen

Learning goals The goal of this minor is to become familiar with various data processing techniques. After this minor, you can make choices in a well-founded manner on which technique suits your client's request so you can present data products convincingly.
Within the minor, various subprojects have been set up, in which you and your group are actively working on these learning objectives:
  • You can research current issues of the target organisation in the data engineering domain.
  • You have acquired knowledge and insight with regard to one or more topics in the data engineering domain that fit into the subjects in the overall lesson plan
  • You show the groundbreaking ability to make the transfer from technical knowledge acquired earlier in the course to a new application domain and as a member of a group with fellow students to devise, design and realize an innovative
    • data collection solution;
    • (information) facts solution;
    • information derivation solution;
    • information delivery solution.
  • You have immersed yourself individually in a data problem, by investigating and analysing the problem, you have chosen an aspect based on your own judgement on the current situation of the problem and the degree of priority and attention given to this by the company.
  • You are able to convincingly present your own innovative solution for the data problem investigated, e.g. in an elevator pitch, so that the audience of experts does not only gain insight into the content technology and the important aspects of the solution, but are also willing to further develop this solution in a follow-up project.
  • You can apply professional feedback in your implementation and justify this in your portfolio

All of the above solutions are fit for a real-life case/situation.

This is a Minor Plus
  • An assignment that can be approached and developed from a multidisciplinary perspective (e.g. communication, design, interactive, economical, business and technical (IT hard/ software)
  • An assignment where the solution is not obvious or has been devised and determined in advance
  • For full time students, we expect students to invest 40 hours a week.
  • For part time students, we expect students to invest 20 hours a week, due to their added experience and efficiency.
  • Students can work at the company for at least 1 part per week and address people there in order to give the assignment a good form.

Ingangseisen

Because we have limited seats in this minor, all students need to send a motivation letter to: t.ubert@hr.nl to be accepted.

For students from: INF, TI, CMGT, BIM and broad ICT bachelor

Additional requirements:

  • Internship passed. (for PT 'Werkpraktijk' year 1 and 2 passed)
  • Minimum of 90 ECTS in the main phase (including internship or 'Werkpraktijk') of the curriculum
  • Working knowledge of relational databases and set theory.
  • Accepted motivation letter.
  • Given the workload of the minor, students should not have retakes or other obligations (for PT it is advised to choose a project at your place of work).
Students from other programs:
  • Internship passed.
  • Minimum of 90 ECTS in the main phase of the curriculum
  • Working knowledge of relational databases and set theory or passed (online) course databases and SQL from Khan Academy, Coursera, EdX, w3schools or code academy and a programming language like python or C# (we can recommend introduction courses to prepare for this).
  • Accepted motivation letter.
  • Sometimes an additional entrance interview.
  • Given the workload of the minor, students should not have retakes or other obligations (for PT it is advised to choose a project at your place of work).
  • Given the workload of the minor, students should not have retakes or other obligations (for PT it is advised to choose a project at your place of work).

Literatuur

  • The New Oil: Using Innovative Business Models to turn Data Into Profit, Arent van 't Spijker, Technics Publications; First edition (July 1, 2014) ISBN-13: 978-1935504825 (ebook)
  • Agile Data Warehouse Design, Lawrence Corr, DecisionOnePress, ISBN 9780956817204 (or https://gumroad.com/l/modelstorming)
  • Designing Data-Intensive Applications, Martin Kleppmann, O’Reilly, Print ISBN: 9781449373320 (1449373321) or Ebook ISBN: 9781491903100 (1491903104) (Third release, 2018)
  • Data als succesfactor, Karien Verhagen, Paul van der Linden, Pearson, ISBN9789043037006 including Mylab (Dutch, English version pending).
  • Cursushandleiding/Course manual

Rooster

To be announced.

Toetsing

Portfolio with a personal and a group assignment

  • Serious game on data quality and metadata (group)
  • Data logistics analysis, design and implementation for a case within client (FT) or employer (PT) organisation. (Individual and group assignment)

Aanvullende informatie

Students from non-IT must have an interest in using data in their working environment and be willing to study (a part of) technical topics concerning data and to learn the technical jargon in the data field of expertise.

Fit for programs

Regular minor:
For students from: INF, TI, CMGT, BIM and broad ICT bachelor

For minor plus:
All programs where data can be a significant part of the working environment.

Website https://www.meetup.com/nl-NL/Rotterdam-data-engineering-Meetup Honours Program Lab (HP-lab)

Do you also wonder how companies get all your data and how reliable it all is and what can be done with data? In the HP lab of the minor Data Engineering you will look at data with a multidisciplinary approach.

The assignment you can work on within the HP lab is a challenging, open and complex practical issue, where the research question or problem definition is not clearly defined. The innovative final solution does justice to the disciplines involved and the context of the problem (target group, users, customers, trends and developments, etc.) This solution is developed in such a way that a case partner can start immediately to begin implementation .

Criteria

• An assignment that can be approached and developed from a multidisciplinary perspective (communication, design, interactive and technical (IT hard / software)

• An assignment where the solution is not obvious or has been devised and determined in advance

• Structure team and time assignment within assignment can be, depending on the HP demands of your program. The team signature (from what programs are students involved) will drive the scope of your project. You will consult with the coordinator of the minor and of HP to finalise the level and scope of your project.

The honours assignments aligned with the data engineering minor will involve at least a data issue. So new technologies and trends (sensoring, Internet of Things, data driven design, data engineering etc.) can be used in the design. Human usage  is central to the design process (human centred, participatory design), where the added value for end user will drive the entire design process. We also address the ethical and legal sides of the design. We like to address not just commercial interests, but also aim at social innovation.

In an equal relationship and cooperation with case partners and students, project supervisors and lecturer-researchers from the Rotterdam University of Applied Sciences, a multidisciplinary way working on an interactive final solution, where the entire spectrum from communication to hardware / software is included in the design. The outcomes (final solutions) for the assignments are the result of an extensive exploration of the context through research (target group, users, customers, trends and developments, etc.). At the start of the assignment it is often not clear what the best solution should be and what the student teams will deliver. An important requirement is that the solution includes a technical element.

In the first trimester the main focus is on exploration of the situation / problem and concept development.

In the second trimester the team will study a final solution, refine it, realize it and test it and eventually present it.

Learning tools and materials
  • The New Oil: Using Innovative Business Models to turn Data Into Profit, Arent van 't Spijker, Technics Publications; First edition (July 1, 2014) ISBN-13: 978-1935504825 (ebook or print)
  • Agile Data Warehouse Design, Lawrence Corr, DecisionOnePress, ISBN 9780956817204 or the ebook https://gumroad.com/l/modelstorming/beam-hr-nl with the discount code: beam-hr-nl
  • Designing Data-Intensive Applications, Martin Kleppmann, O'Reilly, 3rd release 2018, ISBN: 9781491903100 (1491903104) (https://dataintensive.net/buy.html (ebook or print)
  • All materials provided or prescribed via electronic learning environment (LMS), in classes or in (guest)lecture presentations.
  • Notepad (digital is allowed, not recommended), scrap paper and pencils
  • Rules for E-mail etiquette and handing in files into the university's environment in EN (provide in the course manual).
Study load

This course gives you 30 credit points, which corresponds to a workload of 840 hours for all activities (research, execution, consults, collecting and processing feedback, etc). During 2 periods (6 months).

In this minor there will be (guest)lectures, (guest)workshops and labs.

Main language

Materials in English, lectures: depending on student population and guest lecturers English or Dutch.