Consulting firm KPMG and Imperial College London have formed a £20 million partnership to "help transform the UK into a global leader" in big data analytics.
They have launched the "KPMG Centre for Advanced Business Analytics" at the college, with KPMG putting in the money. The project will focus on five key areas - analysis of business capital, growth opportunities, people, operations and resilience.
Each area has been selected to help UK businesses gain a competitive edge "by launching products and services ahead of international competitors", KPMG said. The centre will develop innovative approaches, analytical methods and tools for using big data, giving UK businesses the opportunity to solve complex issues, said KPMG, such as enabling banks to predict fraud or helping retailers better understand consumer behaviour.
The eight-year project will see a joint team working together, with the ambition of completing 15-20 projects per year. Over the life of the project 800 PhD students will be trained at the college to become data scientists.
The centre will be led by researchers at Imperial College Business School as part of the college's Data Science Institute, which is already developing new data science methods and technologies and supporting data-driven research.
As part of the launch, KPMG and Imperial are unveiling a number of initiatives, the first of which is a Global Data Observatory. Created to bring large and complex amounts of data together with data visualisation capabilities, it will allow researchers to spot patterns and get real insights into complex business issues, said the partners.
Simon Collins, KPMG UK chairman, said: "Our collaboration with Imperial is about developing the people and skills to use data to drive new industries and new services."
Professor G 'Anand' Anandalingam, dean of Imperial College Business School, said: "Today's datasets are so big and complex to process that they require new ideas, tools and infrastructures. The KPMG Centre for Advanced Business Analytics aims to address these challenges by looking at how we can translate complicated information and turn it into potential solutions."
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