UK-based Venture Information Management has collaborated with Warwick Analytics on the use of predictive analytics to solve business challenges ‘on a budget.’ The buzz around big data and the internet of things have made decision makers aware of the potential of predictive analytics. But the approach usually means large budgets, long lead-times, multi-stakeholder engagement and a team of data scientists.
Warwick Analytics, a spin-out of the University of Warwick, was built on ten years of academic research resulting in a number of ‘unique proprietary algorithms’ and features that are claimed to position it to solve business challenges ‘without the need for the expensive compute infrastructure that analytics requires.’
The solution is designed to work with dirty or incomplete data without the need for extensive clean-up projects. Data requires minimal manipulation compared to traditional analytical methods. WA’s toolkit classifies unstructured content with an automated information retrieval function. Up to 85% of the analytical process is automated, minimizing the cost of data scientist support.
Venture envisages that the solution has application in maintenance optimization, with real time integration of sensor data, and analysis of maintenance reports and other data to locate the root cause of existing issues in downstream and upstream assets. Another use case is in production optimization, increasing data re-use and review of historic upsets to eliminate loss and reduce inefficiencies. WA’s SigmaGuardian adds a root cause analytic functionality to the offering.
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