Today, analysts seek to derive insight from large, heterogeneous, high-velocity (i.e., big) data sets using varying data analysis methods. These data sets are ubiquitous. They arise due to burgeoning cloud computing services, the anticipated Internet of Services (IoS), and the emerging Internet of Things (IoT). Big data is often defined as any data set that cannot be handled using today’s widely available mainstream solutions, techniques, and technologies.
Currently, there is a shift towards data-driven decision-making in both industry and the sciences. This trend was described in a big data study we recently conducted for the German BMWi (formerly the Federal Ministry of Economics and Technology, today known as the Federal Ministry for Economic Affairs and Energy). In the study, big data challenges and opportunities were classified into five dimensions, namely, technology, application, economic, legal, and social. These are described below.
Technology. There is a need for scalable systems and platforms for data analysis, novel data analysis methods, and in particular technologies to help overcome the skills gap (e.g., enabling data analysis methods to be accessible to a wider audience).
Application. Many novel applications are emerging in the information economy, such as information marketplaces, which refine and sell enriched data. These information marketplaces are effectively bootstrapping the information economy. Other examples include personalized medicine, Industry 4.0, and digital humanities.
Economic. The challenges and opportunities in the economic dimension lie in new business models and content delivery paradigm shifts (e.g., information pricing and the role of open¬-source software).
Legal. From a legal perspective, big data will present many challenges with respect to ownership, liability, and insolvency, in addition to prevalent issues, such as privacy and security.
Social. Lastly, data driven innovation will have a profound impact on society as a whole with respect to social interaction, news, and democratic processes, among others.
The German Study and an English summary can be found at Big Data Management Report
Written by Prof. Volker Markl, Database Systems and Information Management TU Berlin
The European Technology Platform for Software and Services NESSI, together with partners from the FP7 project Big, have drafted a Strategic Research and Innovation Agenda (SRIA) on Big Data Value. The objective of the SRIA is to describe the main research challenges and needs for advancing Big Data Value in Europe in the next 5 to 10 years. The SRIA will be an important channel for providing input to the European Big Data Value Partnership that aims to establish a Public Private Partnership on Big Data Value.
This new initiative should be a common effort and we welcome you to provide your views on the SRIA. Your opinions will be integrated in the final version of the SRIA and presented at the NESSI summit 2014 on 27 May in Brussels (register here).
For background information you can download
We look forward to receiving your input!
Big Data is one of the key research and strategy topics for the world of business. Now 24 Institutes of the Fraunhofer-Gesellschaft, Europe's largest organisation for applied research, have come together to pool their expertise in the new Big Data Alliance, creating a single point of contact for companies, politics and research.