Big Data and Business Analytics
The degree program is oriented towards all company specialists and executives working to establish new spheres of application and involved in project planning and implementation in the field of BI Consulting, Business Analytics, Project Engineering and Information Analysis. You can choose between an extra-occupational track (part-time) with lectures on weekends and a classic full-time study program.
Big Data - of ever greater significance in the corporate environment
The volume of structured and unstructured data available to companies today both from internal and external data sources is growing rapidly. The objective is to utilize this data for targeted sales pitches, in establishing new business fields and in optimizing corporate processes.
Generating knowledge from data
The aim of the degree program "Big Data and Business Analytics" is to ask the right big data questions arising from the specific company context, to identify and analyze the relevant data, and finally to relay the analysis results back to the company in a target-oriented fashion.
What we offer
As a result, apart from technical and statistical tools such as big data architectures, data mining and predictive analytics, the curriculum is also focused largely on creative questioning techniques, visualization, storytelling, ethics and international law. The theoretical knowledge gained is applied and enhanced in a case study which increases in complexity with each semester.
Flexible alongside your full-time career - with online support
To accommodate the flexibility requirements of working professionals the extra-occupational track offers classroom teaching modules taking place at regular intervals over a weekend are combined with online e-learning based on live chats, and self-paced e-learning.
NEW SINCE FEBRUARY 2018: PRACTITIONER TALK SERIES
Beginning in February 2018 Representants from external companies with a strong Big Data context are invited to show the latest development of Big Data practices within their respective company during a talk including a follow-up discussion with the students. Key objective of the talk series is to provide the students with the most recent Big Data methodology, applications and trends in various business branches.
We are delighted to had the following prolific speakers involved with the talk series:
|Apr 13, 5:00 pm - Room T51|
|Zalando||Machine-Learning Fraud Prevention at Zalando Payments|
|Feb 09, 5:00 pm - Room T51||Marcel Dix||ABB Group||Big Data and Data Analytics in Industrial IoT|
|Degree||Master of Science (M.Sc.)|
90 (extra-occupational) / 120 (full-time)
|Duration of Study||
October & April
720 EUR per month part-time / 790 EUR per month full-time + one-time registration fee of 750 EUR
Applicants from countries with a visa obligation need to pay a one-time registration fee of 1,000 EUR and must pay the first year’s tuition fee in advance.
The part-time program is geared to the needs of working professionals. The lecture/classroom modules are mostly bundled at weekends and are supplemented by online coaching. An appointment schedule of the lecture weekends can be found here: starting in October 2017
The full-time program bases on our regular CORE Principles.
|Terms abroad / Internships||
The course is supplemented by case studies carried out in companies. The course does not include a term abroad.
Structure and content of the degree program and course model
The course is divided into 5-week blocks as is customary at SRH University. It comprises a mix of case studies which become larger and more complex with each semester, and is accompanied by classroom modules, the content of which is directly linked to the case studies. In the first semester, students are taught all the required basic knowledge and methods. The second and third semesters are self-contained units.
|First Steps Into Case Studies||6|
|Data Engineering I||5|
|Data Management I||4|
|Data Storytelling and Communication I||3|
|Case Studies I||8|
|Data Storytelling and Communication II||6|
|Privacy, Ethics and International Law I||4|
|Case Studies II||8|
|Data Management II||4|
|Data Storytelling and Communication III||6|
|Privacy, Ethics and International Law II||3|
|Master Thesis Project||18|
The aim of the "Big Data and Business Analytics" course is to ask the right big data questions arising from the specific company context, to identify and analyze the required data, and finally to relay the analysis results back to the company in a target-oriented fashion.
Apart from technical and statistical tools such as big data architectures, data mining and predictive analytics, the curriculum is also focused largely on creative questioning techniques, visualization, story telling, ethics and international law.
The theoretical knowledge gained is applied and enhanced in a case study which becomes increasingly complex with each semester. To accommodate the flexibility requirements of working professionals, classroom teaching modules taking place at regular intervals over a weekend are combined with online e-learning based on live chats and with self-paced e-learning.
The study course is oriented towards all company specialists and executives with responsibility for establishing new spheres of application and for project planning and implementation in the field of big data und business analytics, such as:
- Specialists with a (business) informatics, mathematics or engineering degree who wish to extend their knowledge in the field of business analytics and/or big data analytics and to take on personal responsibility for the planning and coordination of big data projects.
- Business analysts or specialists who work in the wider sphere of "business intelligence" and wish to extend their knowledge in the field of big data engineering, big data management and/or big data analytics and to take on responsibility for the planning and coordination of big data projects.
Apply now to assure your future!
If you are interested in applying for the MSc Big Data and Business Analytics, simply make use of our online application form. You must fulfil the admission requirements to get admission to our degree program. If you have any questions concerning your application, please feel free to contact our office. If you would like more detailed information or wish to arrange a consultation appointment, you can contact the course administration staff anytime.
1) What are the criterias to get an admission?
Just have a look at our admission requirements. Required is a bachelor degree with 180 ECTS credit points in computer science, business informatics or a related field and a minimum of one year qualified and subject-relevant professional experience in one of the following areas: IT, marketing, logistics, production or finance.
2) Is there a mandatory internship?
No, but the course program is organized extra-occupational, so a lot of courses takes place on weekends and you have time during the week to gather practical experience.
3) Are the courses more theoretically or practice oriented?
All specialized courses are a combination of theory and application. In addition, every semester there is a large case study in which the students have to apply what they have learned
4) Which courses are being taught in the full-time-track?
The full-time-track takes place parallel to the part-time-track with a lot of similar courses. Except the courses Big Data programming and Machine Learning, which are only taught in the full-time-track.
5) Is e-learning also available in the full-time-track?
Yes, all materials are available online. However, coaching sessions during the module and the case studies takes place locally, while you are on campus.
6) Payment issues
Total study fees of €18960 are payable in two instalments. First instalment, 1-year fee plus enrolment fee, total of €10130, must be paid in advance. Second instalment of €9480 can be paid within the first year before re-registration for the third semester.
7) Are scholarships available?
It is possible to apply for different scholarships before and after start of your studies. The DAAD scholarship database gives you a wide overview about different possibilities.
The Team of the Master Program Big Data & Business Analytics
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Head of Course
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