The National Centre for Applied Data Analytics (CeADAR) is a market-focussed technology centre for the development, and deployment of analytic technology and innovation. The Centre’s work focuses on developing tools, techniques and technologies that enable more people, organisations and industries to use analytics for better decision making and competitive advantage.
The primary outputs of the Centre are prototypes, demonstrators, alongside contract research plus state of the art reviews of data analytics technology, and best-practice methodologies. CeADAR is funded by Enterprise Ireland, IDA Ireland and by contract research. The Centre is based in and led by University College Dublin in partnership with the Dublin Institute of Technology.
CeADAR has particular strengths in: predictive analytics, machine learning, real time analytics and visualisation. The Centre has an extensive catalogue of technology demonstrators, IP and analytics technology reviews which are all made available to members.
Industry membership of CeADAR has grown significantly in recent years and now totals over 80 industry partners ranging from multi-nationals to indigenous SMEs spanning every industry vertical.
The Centre is also the focal point of a thriving data analytics ecosystem delivering frequent seminars, conferences, consultancy and members’ networking events throughout the year.
CeADAR was awarded the 2016-17 Dunn & Bradstreet prize for Best Analytics Research Group Ireland at the DatSci Awards 2016-17
CeADAR’s 3 core work programmes are in:
1. Visualisation & Intelligent Analytic Interfaces
This research area concerns making the “Analytics disappear” so ordinary users can derive benefits and can explore data, develop insights and communicate results from advanced analytics tools. A major driver is to ensure the right data gets to the right person at the right time in the right medium. Sub-themes within this area are: Beyond the desktop (applying / developing ground-breaking ways of interacting with large complex data sets using more natural interfaces to discover new insights), changing user behaviour based on analytics and passive analytics
2. Data Management for Analytics
This thematic area develops approaches, methods and tools to improve, simplify and reduce the effort involved in the management of data for analytics purposes
3. Advanced Analytics
Advanced analytics is evolving to provide timely, relevant and accurate information to enable real time decision making for organisations. This new analytical capability has the power to provide a competitive edge to organisations. But the advanced analytics story (particularly in relation to big data) is still being written and this research theme is focused on pushing the boundaries out even further. Sub-themes within this area are: knowledge discovery and insight, social media trending and contextualisation challenges, real-time analytics, predictive analytics and cognitive computing