Big Data & Business Analytics

Program Overview

Big Data & Business Analytics

Master of Science (M.Sc.)

Degree Overview

The Master's programme "Big Data & Business Analytics" at FOM University of Applied Sciences is designed to equip students with the skills to analyze, evaluate large and heterogeneous data sets, and use them in a business context. The programme is taught entirely in English and leads to the academic degree Master of Science (M.Sc.).

Locations

• Essen
• Munich

Duration

• 4 semesters, including thesis

Credit Points

• 120 ECTS

Total Costs

• 22,500.00 euro (including registration fee, tuition fee, and examination fee)

Accreditation

FOM University of Applied Sciences is accredited by the German Council of Science and Humanities and was the first private university in Germany to be system-accredited by FIBAA in 2012. This means that all FOM degree programmes are state and internationally recognized. In addition, the FOM University of Applied Sciences has been awarded the "Excellence in Digital Education" seal by FIBAA for its outstanding quality in digital teaching.

Career Prospects

• Big Data Manager
• Business Analyst
• Data Analyst
• Data Scientist
• Business Development Manager
• Big Data Engineer
• Chief Data Officer

Semester Overview

1st Semester

• Big-Data-Architecture & -Infrastructure (5 CP)
  • Enterprise architecture management (EAM)
  • Technological requirements for big data
  • Vital infrastructures for data-driven business models
  • Complex processing by continuous data sets
• Decision Focussed Management (6 CP)
  • Traditional decision theory
  • Management decisions from a psychological perspective
  • Decisions in a strategy context
• Leadership & Sustainability (6 CP)
  • Leadership as part of normative, strategic and operative business management and in the context of diversity management
  • Leadership styles, techniques, and instruments
  • Ethics and sustainability
• Big Data Analytics (6 CP)
  • Data sources and data classification
  • Visual analytics / data discovery / explorative data analysis
  • AI methods such as machine learning
  • Computational intelligence: fuzzy logic, neuronal networks, evolutionary algorithms
• Deutsch (6 CP)
  • Fundamentals in listening, reading, writing, and speaking
  • Basic grammatical skills
  • Application in situations of everyday life

2nd Semester

• Applied Programming (6 CP)
  • Basic principles and application of programming languages for big data: SQL, R, and Python
  • Languages and tools for data management
  • Data integration
  • ETL v. ELT (data lake)
• Analysis of semi- & unstructured Data (5 CP)
  • Crawling and pre-processing
  • Text mining / web mining
  • Social media analysis
  • Ontologies
  • Semantic and graphic modelling/technologies
• Project management of Big-Data-Projects (5 CP)
  • Planning, management, and control of big data projects
  • Challenges, specific features, and success factors of big data project management
  • Architectural and technological features
  • Introduction of big data applications
  • Integration and harmonisation of data sources and planning of data analyses and reporting
• Area of application: Business Analytics (5 CP)
  • Goals and fields of activity for big data applications
  • Sector and type of data sources
  • Application of processes such as association analysis, decision tree process, neuronal networks, cluster analysis
• Ethics & Law (5 CP)
  • Ethical aspects of the use of big data
  • Legal aspects of the use of big data
  • Compliance
• Information-Security (6 CP)
  • Technical Basis
  • Data protection and data privacy
  • Risk analysis / type of threats
  • Attack vectors and scenarios
  • ISMS

3rd Semester

• Big-Data-Consulting Project (6 CP)
  • Selection of an area of application for the analysis project
  • Data storytelling
  • Addressing a management issue
  • Data acquisition, processing, and analysis
  • Preparing findings for management
• Quantitative Data Analysis (5 CP)
  • Qualitative and quantitative research methods
  • Quantitative data analysis (applications with R, statistical test methods, multivariate processes)
• Big-Data-Analysis Project (6 CP)
  • Selection of an area of application for the analysis project
  • Project work with first independently produced data analysis
• Strategic Business Model Development (5 CP)
  • Results of big data analyses as drivers of business model development
  • Planning of big data strategy/business analytics strategy
  • Strategy approaches and strategic planning and management instruments
  • Data-based business models and business transformation
  • Open innovation/innovation management
• Applied Project I (6 CP)

4th Semester

• Master’s Thesis and Colloquium/Defence (25 CP)

Admission Requirements

• University degree with 180 ECTS:
  • with a share of at least 40 credit points in (business) informatics modules
  • or
  • a university degree (in any field) with at least 10 credit points in (business) informatics and relevant professional experience, e.g., in the areas of software development or operations and network administration. Up to ten credit points may be recognised for each year of relevant professional experience, meaning that a maximum of three years of relevant professional experience is sufficient for admission. Admission is possible through a combination of credit points earned in (business) informatics modules and relevant professional experience.
  • or
  • Successfully completed oral admission examination based on a written essay.
• English language level B2

How to Apply

1. Register your personal data and educational background in the application form.
2. For the registration, you need the following documents:

• Authenticated copy of general university entrance qualification certificate and school-leaving certificate or high school diploma
• Curriculum Vitae
• Authenticated copy of bachelor's degree certificate (for details check the admission requirements) and Transcript of Records bachelor's degree
• Proof of sufficient English language skills (at least B2 proficiency level – for details check the admission requirements)
• Only for MBA: Proof of professional activity for at least 1 year after completion of the bachelor's degree (prerequisite)
• Scan of passport

3. Please send all documents as PDFs and name the file as follows: Last name, first name_Study programme (e.g. Smith, Jane_Big Data and Business Analytics).

Tuition Fees

• Total fees: 22,500.00 euro (including registration fee, tuition fee, and examination fee)
• Tuition fee: 22,500.00 euro
  • 1st Instalment (Deposit fee): 500 euro (has to be paid after receiving the invoice in order to secure the admission)
  • 2nd Instalment: 13,257.75 euro (payable immediately upon receipt of invoice before the 1st semester)
  • 3rd Instalment: 8,742.25 euro (payable before the 3rd semester)