Master's program in Big Data

The Master’s Program in Business Analytics / Big Data, accredited by the French Ministry of Higher Education and Research, is founded on CY Tech Engineering School’s expertise in the following fields: Business Intelligence, Decision Support, Business Intelligence and Business Analytics/Big Data.

The program is taught in English and primarily dedicated to non-French-speaking students.  Successful students will graduate with a state-recognized Master's Degree.

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Objectives of the master's program

Business Intelligence and Business Analytics have now become key elements of all companies. 

The objective of this Master’s program is to train future specialists in Information Systems and Decision Support. The program includes solid content in mathematics- and uses a wide range of computer-based tools, which allows students to deal with real problems, analyze their complexity and bring efficient algorithmic and architectural solutions. Big Data is the ultimate game changer.

The targeted applications concern optimizing the processing of large amounts of data (known as Big Data), logistics, industrial automation, but above all it’s the development of BI Systems architecture. These applications play a major role in most business domains such as logistics, production, finance, marketing, client relation management systems.  

The need for trained engineering specialists in these domains is constantly growing and this Master’s program answers this emerging need.

Specifics of the master's program

This Master’s Program has grown from the specializations in Decision Support, Business Intelligence and Business Analytics. 

CY Tech has been ranked amongst the top institutions in France by independent organizations. 

Distinctive points of this course: 

  • Triple skill-set with architecture (BI), data mining and business resource optimization. 
  • This Master’s program will be run by a multidisciplinary group: statistics, data mining, operational research, architecture;
  • Implementation of interdisciplinary projects;
  • Methods and techniques taught in this program come from cutting-edge domains in industry and research, such as opinion mining, social networks and big data, optimization, resource allocation and BI Systems architecture;
  • This Master’s program is closely backed up by research: several students are completing their final study project on themes from the L@RIS laboratory, followed and supported by members of the laboratory (PhD students and research professors);
  • Being familiar with the tools used in industry dedicated to data mining, operational research and Business Intelligence gives the students an advantage in their employability after graduation;
  • Industrial partnerships with companies strongly involved in Big Data are an integral part of this program : 
    • SAS via the academic program and a ‘chaire d’entreprise’ (business chair), allowing our students access to Business Intelligence modules such as Enterprise Miner (data mining) and SAS-OR (in operational research).
    • SAP via our University Alliance Program, enabling our students’ access to the latest versions of BI modules from SAP, such as SAP-BW and SAP-Business Objects.
Course structure

The Master's program includes two semesters :

  • A series of modules at Master II level validating 60 ECTS. The academic year starts in September.
  • An internship including the presentation of a Master Thesis.
Course Catalogue
Teaching methods

All lectures will be taught in English with the exception of the FLE (French as a Foreign Language) course, which aims to teach students to understand and express themselves in French as well as to get to know the French culture. 

Students will also be familiarized with the 3 pillars of the Big Data Master's program:

  • Modeling, operational research and decision support.
  • Data mining and data mining.
  • Business Intelligence.
Master's program overview

This Master’s program is based on the three pillars, mentioned above, except at a higher level of expertise. To train experts in our field, we provide students with professional skills in modeling, design and implementation of IT architecture, data mining and optimization.

Course Catalogue

 

Semester 1

Skills

Lectures

Hours

ECTS

Computer Technologies

Advanced Data Base 2 (PLSQL, Transaction, Distributed Database)

24

8

NoSQL

20

Machine Learning with Scala

20

Data Exploration

Data Mining Approach (Time series, logistic regression, Bagging Boosting, Random forest, Neural network)

21

7

Semantic Web and Ontology

21

Social Network Analysis

15

Business   Intelligence

Advanced BI & Data Visualization

24

4

Operations Research

Forecasting Models

33

5

SAS Analysis

12h

Foreign Languages & HR

FFL: French as a Foreign Language

26

3

PPP: Personalized Professional Project

15

Agile Methodology

7

Autonomous Work

Master thesis preparation 

12h per week

3

Total M2: Semester 1

278

30

 

Semester 2

Skills

Lectures

Hours

ECTS

Data Exploration

Elastic Search Kibana

21

5

Text Mining and Natural Language

18

Deep Learning (Convolutional Neural Network, Tensor flow, Keras, ..)

12

Operations Research

Supply Chain

18

5

Constraint Programming

18

Multi-Objective Optimization

18

Game Theory

10

Software and Architecture

Big Data and Advanced Analytics

42

4

Foreign languages  

FFL: French as Foreign language

21

1

Total courses in M2 

157

12

Autonomous Work

Master Thesis & Final Project Defence

12h per week

6

Internship (22 weeks minimum)

9

Total M2: Semester 2

30

Internship

Internships will be supervised by a university professor. A minimum of 3 meetings will take place between the trainee, the school representative and the person in charge of the company/research laboratory. Each meeting will result in a professional presentation of the trainee, which will lead to an assessment.

In addition to these meetings, the student will be required to write an internship report which will contain the following :

  • a presentation of the company/laboratory;
  • a presentation of the activities and goals;
  • an analysis and synthesis of the work undertaken;
  • a personal analysis of the internship: what worked and what did not work.

This internship will last a minimum of 22 weeks. 

Admissions requirements

Admissions to our Master’s degree in Big Data (Data Analytics, Data Science, and Data Architecture) will be open to students who have previously validated a 4-year Higher Education diploma (i.e. 240 ECTS or equivalent regarding non-European students) and have strong skills in Mathematics and Computer Science. 

The documents to be sent are as follows :  

  • Official copies of university transcripts and degrees.
  • Copy of identity card/passport.
  • A one page CV.
  • Your letter of interest (max. 2 pages).

Your letter will help us to know about you, your interests, your values and goals.  You will explain what encourages you to study a Master's program in Business Analytics at CY Tech.

  • One letter of recommendation

If you have not yet graduated from your current degree you will need to ask your Home University for a transcript of records corresponding to the level of studies you have obtained. If admitted, you will have to provide us with the original documentation.

  • Proof of English language level via an official external exam (TOEIC 800, IBT TOEFL 80, IELTS 6.0) 
Some applicants might be exempt from providing us with a Proof of English language level if their mother tongue is English or if they have studied a fully-taught English program.

How to apply

Candidates must submit their application by clicking here, and at the latest on June 30th, 2024 for our September session.

Shortlisted candidates will be notified after sending applications and will be accepted after the file evaluation. 
Selected candidates will be contacted for an interview. 
After being admitted candidates will receive an admission letter.

Tuition fees

The tuition fees for one academic year of the Master’s program are 7 000 €.

2000 euros will have to be settled following the admission in order to start the registration process.

Job opportunities

A large number of companies need to control BI Systems in order to monitor their activities. Both public and private organizations have to tackle more and more constraints which include new and stricter rules & regulations. Competition is tougher and needs for multiple optimizations are essential for good business practices. 

The specialists in this area are looking for experts in the domains of analytics, such as statistics, prediction, data mining, operational research in order to comply with the issues and needs of large companies in areas such as risk, fraud, customer relations and marketing. 

The growing and larger demand in these domains offers graduates from this Master’s course numerous and diverse job opportunities –in areas linked to decision support- such as  Data Scientists, Consulting Engineers, Research and Development Experts, Tool Design Engineers, BI/Business Analytics Solutions Providers, or simply Users of Business Intelligence tools. 

Graduates who wish to specialize in the area of research can start a career in both public and private research centers, find a position as researchers in Higher Education or prepare for additional education at the doctoral level.