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“ Think of data aggregation and then using machine learning to detect trends and patterns that allow you to predict likely business outcomes . So you could potentially predict when the next flood hits , you could predict all kinds of things depending on your specific situation ,” says Kederer .
In the context of energy , and the highly volatile nature of the current market – as seen during major network disruption – organisations can firstly follow the necessary step of migrating their data to a strategic , more efficient hosting , then consider further ways to optimise this and understanding the use-cases for data in predicting disruption and forward-planning for risk management .
“ This is where our system architects work with our customers and our partners to really optimise the architectural decisions . In some cases , the code that runs takes up all this energy . So migration is the foundation you optimise . But at the end of the day , the issue that we ’ re facing in climate is a data issue . The data is core to addressing this ,” Kederer says .
108 December 2023