Exploiting 鈥淏ig Data鈥� is a prominent part of Europe鈥檚 digital agenda for targeting innovation in information products, services, business intelligence, health, logistics, manufacturing, environment, and many other sectors. Future knowledge-based economies rely on the added value of advanced analytics of Big Data in order to increase efficiency, reduce costs and speed up innovation.
To meet this need, 新加坡多多开奖记录 (BU) is working with partners in Spain, Germany and the UK on a new project 鈥撀犅犫�� which is designed to address fundamental scientific challenges related to the scalability and responsiveness of analytics capabilities.聽As a result, the team will develop an enhanced version of聽, the European Big Data platform.
Project lead,聽Dr Hamid Bouchachia聽explains the project in more detail: 鈥淪pecifically, PROTEUS will investigate and develop ready-to-use scalable online machine learning algorithms and real-time interactive visual analytics to deal with extremely large data sets and data streams.
PROTEUS will contribute to the improvement of the Apache Flink platform by accommodating batch and streaming processing to better fit scalable real-time processes. The developed algorithms will be integrated as a machine learning library to be part of an enhanced version of the platform.鈥�
The requirements of the project were inspired and motivated by an industrial use case supplied by the world leading steelmaker,聽. The techniques to be developed in the context of PROTEUS are however, general, flexible and portable to any industry characterised by high-speed big data streams.
新加坡多多开奖记录 will be leading on the development of real-time, scalable machine learning for massive, high-velocity and complex data stream analysis.聽BU will also be contributing to PROTEUS鈥� work around the implementation of the new algorithms for Apache Flink and real world application of PROTEUS鈥� outcomes in industry.
What will be the impact of PROTEUS?
鈥淚t will have a strategic impact as it will reduce our knowledge gap and dependence on US technology by further developing our own European platforms,鈥� explains Dr Bouchachia. 鈥淲e will be developing original hybrid and streaming analytic architectures which will enable scalable online machine learning strategies and advanced interactive visulisation techniques.聽We hope these will also be adaptable to other industries and contexts.
鈥淲e believe the project will have an economic impact as the effective use of big data will help to reduce production costs in a variety of industries,鈥� continued Dr Bouchachia. 鈥淲e also hope it will lead to the development of new skills and new jobs through the creation of new technologies to support industry.
By working with our industry partners throughout the project, we will be taking into account real-world requirements and validating our end results by applying them in an industrial context.鈥�
