3 Terms + Capstone Project
Master in Big Data Analytics for Business Program
The Master in Big Data Analytics for Business is designed to help participants mastering the business knowledge, the methods and the analytical tools to convert BIG data into BIG insights in marketing, finance and operations.
The program is offered on a full-time basis and consists of 3 terms of academic courses and a professional experience. The curriculum is developed around core modules in business, technology, and methodology, as well as specialized courses in marketing, finance, and operations.
In a connected world, data provide companies with the opportunity to align their marketing, finance and operations strategy with objective facts and figures. Participants will learn how to become data-driven managers, and will be able to spot analytical opportunities in a given business context.
The program is offered on a full-time basis and consists of 3 consecutive terms of academic courses followed by a professional experience.
The course tackles the basic principles of the project management field. Project management is a managerial discipline that is inevitable in a data-driven business context nowadays. In multiple industries as diverse as retail, financial services, pharmaceuticals, software and aerospace, analytical projects drive business. Effective project management often translates into gleaming new opportunities that often translate into increased sales.
This course introduces the participants to the field of business analytics by using a strategic angle. Various case studies are exposed to the participants to let them critically reflect how data science might deliver added value for companies.
> Solve professional dilemmas using concepts of CSR and ethics
> Generate sustainable solutions for organizations
> Demonstrate an international mindset
> Successfully collaborate within a intercultural team
> Convey powerful messages using contemporary presentation techniques
> Assess the values of the organization in which they work
This course zooms in onto the most important aspects of data privacy in the context of the General Data Protection Regulation (GDPR). At the end of the course, the participants know how to treat (company) data in an ethical and responsible way when performing data science.
This course covers how to leverage company data to create value and to build a competitive advantage. At the end of the course, participants are able to understand and manage the data lifecycle, and to implement a data strategy for a given company setting.
This course gives insight into the various real-life aspects of big data analytics. Real-life case studies are presented to reveal best practices for big data analytics. At the end of the course, participants have a better view on spotting big data analytical opportunities in business.
The course introduces its participants to advanced spreadsheet analysis. In- and out-company data is floating around, and the skills to treat that data in an efficient and effective manner is imposing employees to sharpen their analysis skills. At the end of the course, participants do master how to treat data using a spreadsheet analysis tool like Microsoft Excel.
This course covers the concepts of a relational database and the industry standard Structured Query Language (SQL). In addition, this course gives its participants the necessary skill set to visual analytics using the Tableau software.
This course covers the principles of big data and introduces its most important IT tools. The participants are exposed to leading concepts and technologies in the field of big data like Hadoop, HDFS, Spark architecture, Hyve, Keras and Tensorflow, graph databases and streaming.
The objective of this course is to introduce participants to SAS programming. At the end of this course, participants are fluent in SAS programming.
The objective of this course is to introduce participants to Python programming. At the end of this course, participants are fluent in Python programming.
The objective of this course is to introduce participants to R programming. At the end of this course, participants are fluent in R programming.
This course introduces its participants to the building blocks of descriptive and predictive analytics. Nowadays, there is a tremendous increase in customer/company information which is available to the data scientists. This course introduces fundamental analysis methods to describe “what has happened” based on historical data (descriptive analytics), and introduces the fundamental concepts of predictive analytics to the participants.
The aim of this course is to present a concise description of popular time series forecasting models that are based on the regression framework.
This course introduces how network data delivers value in business decision making. At the end of the course, participants are able to scrutinize network data, build a (social) network, and draw relevant conclusions.
This course offers its participants a profound introduction to deep neural networks. At the end of the course, participants are able to spot opportunities to apply deep learning in a real-life business context, while being able to implement them successfully.
This course introduces various visualization tools to reveal hidden patterns in complex data structures or to help in opening black-box algorithms. At the end of the course, participants are able to improve decision making by proposing data science solutions that are performant and interpretable for the business decision maker.
Natural language processing is a flourishing subdomain of data science. This course introduces how textual (company) data delivers value to businesses and details the various data preprocessing steps on how to convert text to a numeric format that could then be used in traditional data science methods.
This course introduces the participants to various statistical and machine learning algorithms for data –preprocessing, modeling and evaluation. This is a fundamental course in the curriculum as it delivers theoretical and hands-one experience in applying basic to state-of-the-art algorithms on various prediction problems.
In this course, the participant learns about the design of recommender systems: the underlying concepts, design space, and trade-offs. A participant should understand the design space of recommender systems and be able to provide design recommendations for a particular application domain, as well as critique a design to point out its strengths and weaknesses.
This course introduces the participants in the field of credit scoring. Nowadays, various information is available within the organization to focus on a data-driven approach to assign a credit risk to consumers of the company.
This course provides an applied perspective on mathematical programming (MP), instead of focusing on algorithms. In particular, it serves 3 purposes: (i) providing a selective catalogue of practical MP problems faced by managers, (ii) linking these problems to the different types of mathematical optimization methods, (iii) formulating MP problems and interpreting their solutions within a spreadsheet.
This course delivers the participants a unique and hands-on experience of solving a real-life data science challenge for a company. The participants do work in teams in a four-month like hackathon projects to deliver a data-driven solution that is acceptable by both the data scientists and the business managers. The supporting staff is composed of both academic and company supervisors.
The course is designed to immerse students into the daily life of business consultants working for an ERP implementation company. Through interactive lectures, group assignments, and the intervention of four expert professionals, this course confronts students with the diverse expectations, tasks, and challenges functional consultants need to tackle. Combining theoretical concepts with hands-on exercises on a hypothetical business case, participants are expected to acquire knowledge on and experience with ERP deliverables and domains (i.e., Microsoft Dynamics 365), workflow design for top-level business processes (i.e.., Procure-to-Pay, Order-to-Cash), project management activities, and functional consulting analysis tools (e.g., XMind, Bizagi).
The Career Program aims to help participants build and implement their professional objective in line with their aspirations, skills and the socio-economic reality of the market.
The objective is to facilitate their integration into the company, in an environment that allows them to develop personally and professionally.
It includes a cycle of thematical events creating bridges with companies and helping students to develop their network.
Our pedagogical approach is an alternation of teaching methods to promote learning in line with the teaching and learning strategy of the institution.
Creativity is one of the critical components of an organization’s ability to survive and thrive in today’s competitive and dynamic markets. This course will provide participants with a rich understanding of how creativity can be facilitated and managed in a work setting. They will acquire knowledge regarding various theoretical conceptualizations (i.e., how do you define creativity), antecedents (i.e., what makes you and others more creative) and outcomes (i.e., what is the impact) of creativity as well as knowledge on design thinking techniques and tools to lead teams in the creative journey.
How do creative ideas happen? How can we foster our creativity and the creativity of those around us? What are the paths of creative development of individuals who are successful in their creative endeavours? What are the implications for fostering and managing creativity in the workplace? What are the obstacles to creativity? What is the nature of creativity in teams and organizations? These are some of the questions we will address. During the course, a variety of teaching and learning techniques will be used to enable participants to think critically and imaginatively about various perspectives of creativity. To realize the goal of a shared learning experience between participants and the instructor, the course is aimed at integrating real challenges and practical experiences of creativity, projects, presentations, experiential exercises, and critical reflection on the various course materials.
This course provides participants with a profound understanding on entrepreneurship, new business development, and business plan writing. Through lectures, testimonials, field-work, and group assignments, participants are confronted with the how, where, when, whom, and why of starting and developing new business activities. As part of an international and multicultural team, participants are invited to work on an operational business plan aimed at either the creation of a new venture (NVC-track) or the acceleration of new business for an already established SME (NBD-track). This course’s ambitions thus go beyond providing theoretical insights. Hands-on experience is gained through out-of-class field work covering all steps of the entrepreneurial decision-making process (e.g., idea generation, feasibility analysis, industry study, market analysis, marketing plan, production plan, product development, and financial statements). In doing so, participants accumulate entrepreneurial knowledge and behaviours that support innovative solutions and new value development.
French language lessons for all levels are included in the program for international students. French is the mandatory choice for all non-French speaking students, while for French speaking students, other languages will be offered and credited as well (Chinese, Spanish, German – list subject to change).
Capstone Project: 4-to 6-month internship or work experience anywhere in the world. Alternatively, students can opt for a consulting project or a thesis.
Please note that courses are subject to change; please check with the local contact if you have any questions.
Zoom on… An integrated business project
The Master in Big Data Analytics for Business offers its participants a real-life consulting assignment at the end of the academic year. This project has the intention to put the competences and skills absorbed over the academic year into practice. In collaboration with a company, participants have the opportunity to solve real business problems using the various techniques and methods that they have acquired.
Last academic year, the project was organized in the form of a four-month data science hackathon. Previous supporting companies are Microsoft, Graydon, Mealhero, Delaware Consulting, Oney, Cofidis, Crédit Agricole, Port of Antwerp-Bruges, The Royal Belgian Soccer Association, Enfocus, Mobly, Monabanq, and many others.
Workshops and Corporate Events
Alongside the courses, the program includes various workshops and corporate events to further develop your personal and professional skills. These cover a range of topics, such as conflict management in cross-cultural environments and intercultural communication.
Our Career Program helps participants to establish their professional career plan by working on their skills, personal strengths, and using networking tools to be prepared to meet recruiters’ expectations internationally.
During their internship, students are able to combine theories of management with hands-on experience and apply the cross-cultural skills they have developed at IÉSEG.
Big Data Engineer, Customer Data Analyst, Data Analyst, Data Architect, Data Quality Engineer, Data Science Researcher, Data Scientist, Online Marketing Analyst, Performance Analyst or Pricing Intelligence Analyst for example: the internship opportunities offered by the program at the end of the curriculum are multiple.
Some companies which hire our interns: Trivago, Accenture, Teradata, Honda Europe, Bombardier, KBC, Materialise, Pipecandy, McAfee, CapGemini, Allianz, Sodexo, BNP Paribas, Bloomon, Auchan, AXA, etc.
The internship can be undertaken in France or abroad. Most students have done their internships in Europe or in Asia for example.
IÉSEG is proud to be partners with Capgemini, SAS and Air France for its Master in Big Data Analytics for Business program.
These partnerships with some of the world’s foremost leaders in data science and analytics enriches participants’ views on big data analytics for business. Partners will share their expertise, professional perspectives and insights on current trends in their field of expertise with participants through coaching sessions, guest lectures, real-life case studies and company visits.
The opportunity to learn about concrete professional issues from business leaders and to gain exposure to the real-world experience of successful practitioners are key assets of the program.
In 2022, IÉSEG Students from the Master in Big Data Analytics for Business won the SAS Curiosity Cup, a competition among international universities and business schools whose purpose is to motivate students to use SAS and come up with insights on topics of their interest.