Olivier Dupouët, academic director, presents the key points and strengths of the programme.
What is Data Analytics?
Data Analytics is based on the statistical processing of information, allowing companies to improve their performance. There are different qualitative and objective analytical methods, and their collection allows the transfer of numerical data and models. The processing of these data is used in the different stages of a product's commercialisation:
- for competitive intelligence purpose
- in the analysis of market trends
- in the strategic decision-making process
- in assessing customer satisfaction
Organisations are therefore able to make evidence-based decisions and offer innovative products and services that best meet consumer needs.
A sharp focus on data for business
Regardless of their size or sector of activity, companies are facing numerous challenges caused by digital transformation. To meet these challenges, tomorrow's professionals will need to bring a wide range of expertise, including statistical data, digital technology, business strategy and management.
The new "MSc Data Analytics for Business" programme, which will be taught in Bordeaux from the start of the 2022 academic year, focuses on the creation of value from the exploitation of data. It provides an opportunity to learn the tools needed to solve real-life problems, and to use the latest mathematical and IT tools to do so. Technical skills, which are at the heart of the programme, are consistently combined with practical application. This innovative pedagogy allows students to gain a better understanding of how to use data in a commercial context.
Preparing today's students for tomorrow's jobs
Graduates of the MSc will thus be able to transform data into knowledge, and knowledge into strategic decision-making, which will lead to the operational implementation of the company's activities. These highly sought-after skills will enable them to access positions in management, team management or international projects:
- Project manager and project management assistance
- Project manager and product owner
- Consultant, advisor in AI development
- Manager of data scientists
- Business engineer in the field of AI
- Digital transformation
