Real-time decision-making tools in the era of “big data”
In our world of connection and mobility, we are generating phenomenal quantities of data. Its sources range from smart phones, social networks and online transactions to digital imagery, geopositioning systems, and many others. The information can be valuable raw material for organizations. However, its multiplicity can make decision-making hugely complex, and existing tools don’t allow decision-makers to use all this data effectively in real time.
Dr. Andrea Lodi, Canada Excellence Research Chair in Data Science for Real-Time Decision-Making, and his team’s work to develop new tools and methodologies will allow enormous volumes of data from multiple sources to be processed and analyzed in real time—in order to obtain useable knowledge and to automate decision-making.
By combining processes for analyzing highly targeted data and real-time decision-making, their mathematical model-based tools will help organizations improve performance, by creating highly customized outputs and taking into account the environments, needs and individual behaviours of their clients or users. The tools will also help improve supply processes and resolve unforeseen problems.
The applications that result will foster new business models that are based on accurate depictions of user behaviours and expectations, combined with competitors’ responses. The many sectors that could benefit include transportation management, energy, health care and manufacturing, as well as supply chain management and logistics.
Lodi’s projects have already piqued considerable interest among numerous industrial partners.
With a multidisciplinary approach benefiting from the collaboration of research teams around the world, Lodi is also helping advance combined knowledge in various disciplines, including constraint-programming; automatic learning; statistics; data-mining; heuristic and metaheuristic methods; and discrete event simulations.