Jennifer has spent many years at SAS working as a pre-sales consultant in a range of different industry sectors including telecommunications, pharmaceuticals, media and services. A lot of her work has been in the B2C sector, with a huge focus on predicting customer behaviour to support marketing and risk management. Her work with the energy sector started off with a focus on energy retailers. But what she found particularly fascinating were the complex dynamics of having to balance reliability and cost against the increasingly urgent need to transition to renewable energy sources. The innovation required to balance increasingly volatile energy supply and demand got her seriously interested in the potential of using IoT data to help manage energy – this includes the whole ‘smart’ paradigm of Smart Grid, Smart Homes and Smart Cities. She then started exploring the whole buzz about IoT in more detail. It quickly became evident to her that the application of Artificial Intelligence and Machine Learning techniques to IoT data has huge potential to change our world for the better: not just in energy management, but across all sectors - from health care to financial services and everything in between. One particular area of focus is in Manufacturing, with the huge potential of Industrial IoT to revolutionise efficiency and reduce waste. Jennifer heads up the IoT practice for SAS UK & Ireland. Jennifer holds a Bachelor Degree in Mathematics and Drama – which she feels to be a perfect combination for someone whose job it is to communicate the power of analytics to businesses.
Real value comes from data when you can start integrating disparate data sources together.
Data collected during the manufacturing process is used to try to identify the cause of discrete problems after the event.
What leads to development of Machine Learning and Artificial Intelligence techniques to find complex patterns in data?
