While today's attention mainly goes to examples by major internet companies such as Google, Amazon or Facebook, data science might be even more relevant in other industrial domains and is definitely relevant for SMEs as well. During our mastercourse we give you the details!

Data are flooding almost all sectors of our economy. That is why an increasing number of innovations is based on managing and interpreting (available) data, which are collected by various means. Are you eager to find out what data innovation can mean for your company, products, services and technology? Discover it during our new edition of our mastercourse cycle 'Data Innovation beyond the Hype', starting in January 2019.

Although 'Digital Transformation' and 'Industry 4.0' lead to transformation, many companies still struggle with actual implementation and how to use their product data to their advantage. To help these companies and increase their competitiveness, Sirris, Hahn-Schickard and the Forschungszentrum Informatik have initiated the collective research project 'InsightProducts - Actionable Insights into Product Service Delivery’.

The 1970s brought us the mainframe, the 1980s the PC, the 1990s the Internet, the Millennium the social/mobile Web - albeit a potentially arguable evolution - and the 2010s introduced us to the bitcoin and the blockchain. What exactly is the blockchain? And how come, despite its enormous potential, its industrial adoption (in Belgium) is lagging behind?

Despite what you might think, there are no quick, simple, off-the-shelf data solutions. Data science is a creative process involving a lot of trial and error tasks. Data Analytics goes beyond technical skills, human, business and research aspects must also be taken into account.

With the development of the Internet of Things and big data, increasingly more data is being collected in more domains. Therefore, over the years, more and more methods to extract useful information from this data have been developed. Some of the most successful methods belong to the pattern mining topic.