30K217 :Advancing Society: Digitization and Big Data Analytics

General info

Instruction language English
Type of Instruction Lectures and Tutorials (Lecture schedule)
Type of exams (Examination schedule)
Course load:6 ECTS credits
Blackboard InfoLink to Blackboard (When you see 'Guest are not allowed in this course', please login at Blackboard itself)


dr. S. Angelopoulos


In the networked context we live in, millions of transactions and behaviours are being recorded daily by a large number of networked sensors and devices. Such data are related to ourselves, our friends, our preferences and our location, and can include intimate information about us, such as our sleeping or eating habits. In addition to this, every day internet users from around the world collectively send more than 45 billion emails, submit more than 95 million tweets, and generate 2.5 quintillion bytes of data, and this is only set to grow. As the data accumulates, the management and strategic leverage of such information resources becomes a critical success factor in creating competitive advantage. This ability to harness vast collections of data is expected to give rise to new opportunities for economic and societal value creation. It has already given rise to a total of 4.4 million jobs globally to support Big Data Analytics, whilst the technology and services it spurs are expected to project growth rates at about seven times the value of the overall Information and Communication market. Real world problems, however, are usually complex and often ill-defined, since they do not come with labels, and the only objective reality is data, which in itself may be incomplete and of questionable quality, making Data Science and Big Data Analytics the profession of the future.

In this course, we focus on advanced applications to understand complex problems in broad areas including social sciences, life sciences, and the management of Big Data. More specifically, we explore cases related to healthcare and sports management, crime prevention, online dating, finance and operation management, as well as many more. You will have the opportunity to understand how high-performance methods are developed and applied to solve complex problems, improve decisions, and ultimately add value to institutions and individuals. A large part of the course is dedicated to Data Science and how to use data storage and data analysis in a smart way, and learn about its intriguing possibilities but also the limitations.

Recommended Reading

  1. Bertsimas, D., Allison, K.O. & Pulleyblank, W.R.,., The Analytics Edge, Dynamic Ideas LLC., 2016.

Compulsory for

  • BSc EBE, track Commercieel Management ( 2016, 2017 )
  • BSc EBE, track Economics and Society ( 2016, 2017 )
  • BSc EBE, track Financial Management ( 2016, 2017 )

Recommended option for