Many businesses, organisations and government departments are increasingly interested in unlocking the value of big data analytics to gain a detailed insight into their stakeholders and market trends. However, this fascination with Big Data (BD) and desire to be seen at the forefront of new technology is leading many companies, as well as a number of projects supported by public funds, into wasteful investments and inefficient use of staff and resources.
We argue that part of the problem is that key decision-makers approach the process of discovering and leveraging useful business information from data in the same way as oil discoveries; given sufficient investment of financial resources, they will eventually yield the knowledge required to realise the gains.
In the context of critical infrastructure, autonomous systems or advanced consumer products, meaningful discovery in applied machine learning and data science is about working on well-defined challenges, maximising existing systems and data sources and embedding existing human knowledge into the analysis and verification stages of big data. Examples of such strategic partnerships include ReFLEX Orkney, the UK’s largest whole system project wherein partners support the creation of solutions from Big Data Analytics (BDA) with the clear aims of supporting decarbonisation, social justice and equity in the energy transition, and resilience in energy services. Another example is the ORCA Robotics – Robot and Asset Self-Certification, wherein well-defined capability challenges from the industry shape the research and verification of autonomous systems and AI solutions.
Read the Full Article Here.