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Academics Master's Degree Big Data and Business Analytics

NEW Practitioner Talk Series since February 2018

Big Data and Business Analytics
Master of Science (extra-occupational or full-time)

Big Data and Business Analytics

Apply now LECTURE SERIES - PRACTITIONERS INSIGHTS: Patrick Baier & Henning Esser (Zalando Payments SE) - Machine Learning-based Fraud Prevention at Zalando Payments Download info material Barbara Sprick

Your Contact for Courses

Barbara Sprick

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 announce the following prolific speakers, who have already confirmed their involvement with the talk series:

DateSpeakerCompanyTitle
Apr 13, 5:00 pm - Room T51

Patrick Baier

Henning Esser

ZalandoMachine-Learning Fraud Prevention at Zalando Payments
Feb 09, 5:00 pm - Room T51Marcel Dix ABB GroupBig Data and Data Analytics in Industrial IoT
Apply now LECTURE SERIES - PRACTITIONERS INSIGHTS: Patrick Baier & Henning Esser (Zalando Payments SE) - Machine Learning-based Fraud Prevention at Zalando Payments Download info material Barbara Sprick

Your Contact for Courses

Barbara Sprick

  • Overview
All facts at a glance
Overview
Degree Master of Science (M.Sc.)
Credit Points

90 (extra-occupational) / 120 (full-time)

Duration of Study

2 years

Starting

October & April

Study model Extra-occupational
Entrance criteria

extra-occupational / part-time: bachelor degree with 210 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. If you have gained a bachelor degree with 180 ECTS credit points, you can make up for the missing credit points and qualifications if you can provide proof of several years of work experience or completed further training courses.

full-time: 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.

Languages English
Tuition fees

extra-occupational or part-time €670 per month

full-time €790 per month

non-recurring registration charge of €650

Course Characteristics

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.

Content, objective and process of study

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.

Study course schedule starting in October

Study course schedule starting in April

Module guide

Year 1
ModuleCP
First Steps Into Case Studies 6
Analytics I6
Data Engineering I5
Data Management I4
Data Storytelling and Communication I3
Case Studies I8
Analytics II6
Data Storytelling and Communication II6
Privacy, Ethics and International Law I4
Year 2
Module CP
Case Studies II8
Data Management II4
Analytics III 6
Data Storytelling and Communication III6
Privacy, Ethics and International Law II3
Master Thesis Project18

 

Business proximity

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.

Interdisciplinarity

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.

Practical focus

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.

E-learning

Click here to access the e-learning platform

Career, perspectives

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.
Application

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.

The Team of the Master Program Big Data & Business Analytics

Prof. Dr. Herbert Schuster

Gerd Moeckel

Prof. Dr. Gerd Moeckel, Studiengangsleiter Applied Computer Science

Fallback Kontakt

Prof. Dr. Ajinkya Prabhune

Barbara Sprick

Prof. Dr. Barbara Sprick, Studiengangsleiterin Big Data & Business Analytics

Anke Schuster

Prof. Dr. Anke Schuster, Studiengangsleiterin Wirtschaftsinformatik

Program concept

Questions? Contact us.

Head of course

Barbara Sprick

Prof. Dr. Barbara Sprick

Professorin

School of Information, Media & Design

Director of studies Big Data & Business Analytics
Room arc215
Ludwig-Guttmann-Str. 6
69123 Heidelberg
Telephone +49 6221 88-2203
Fax +49 6221 88-3648
Send an e-mail

Course administration

Bianca Staffen

Organisation

School of Information, Media and Design

Program manager Big Data & Business Analytics
Room arc212
Ludwig-Guttmann-Str. 6
69123 Heidelberg
Telephone +49 6221 88-2130 Send an e-mail