Data is the black gold of the 21st century. We need to understand and manage the technologies that enable us to collect, secure, analyse and extract information from it.
Head of the Big Data & Analytics Major
The data revolution
Big Data (or massive data) coupled with Machine Learning is revolutionizing the use of data. Even if the principle of analyzing and processing a large amount of data to extract information is not a new process, it relies in the era of Big Data on infrastructures in technological disruption. We can now process gigantic volumes of data, at an incomparable speed, while integrating a variety of structured or unstructured data (images, videos, sounds, texts, logs, etc.).
The objectives of the training
- Understanding the limits of vertical growth in information systems
- Master Big Data frameworks such as Hadoop and Spark
- Understand the concepts of Big Data and the mechanisms of data governance
- Master Machine Learning algorithms and data analysis and manipulation tools (R, Spark, Python, Matlab, etc.)
The Big Data & Analytics major trains engineers who are capable of supporting companies in their digital transformation process by implementing “Datalakes” projects and analytical applications. These paradigm shifts bring a better understanding of governance issues and data quality.
- Advanced web technologies
- Advanced databases
- Operating systems
- Computer networks
- IT Infrastructure
- DevOps with SRE
- Machine learning
- Security of information systems
This training is also available as an APPRENTICESHIP.
Discover the training in pictures
Focus on Jean-Michel BUSCA, Head of the Big Data & Analytics Major
An Ensimag engineer (1988) and a doctorate from the Pierre and Marie Curie University (2007), he began his career at Capgemini, where he worked as a project manager and technical agency manager on the development of online services for the general public, including the electronic directory. Passionate about science, he then turned to research, and studied at LIP6 and Inria peer-to-peer systems, coherence and large-scale data replication, and participated in the European research project Grid4All. Since 2009, he has dedicated himself to teaching and has put his experience in industry and research at the service of students.
Some examples of opportunities
- Big Data Project Manager
- Big Data Architect
- Data scientist
- Research engineer in computer vision and deep learning
- Data engineer