It's true that organizations are getting more out of their data than ever before (as investing more into their data, too), empowering data science and business intelligence teams to explore, visualize, and gain insights into unprecedented amounts of data. Two other things are also true: More is being expected from such teams to differentiate themselves from their competition and that all too often these analytics teams end their projects too soon – failing to consider the decisions their analyses inform. That’s where Decision Analytics comes in, and particularly, Mathematical Optimization.

Key topics include: