The extraordinary spread of computers and online data is changing forever the way that important decisions are made in many organizations.
Hospitals now analyze online medical records to decide which treatments to apply to future patients.
Banks analyze past financial records to learn to spot future fraud, while factories analyze past operations to learn to produce higher quality goods. While a first generation of data mining algorithms has already been developed and is gaining widespread commercial use, we expect future advances to dramatically increase the role of data mining throughout society. Today's demand for data mining expertise far exceeds the supply, and this imbalance will become more severe over the coming decade. Unfortunately, current degree programs in traditional disciplines fail to provide the kind of curriculum needed to train tomorrow's leaders in this area. The problem is that data mining requires a rich, interdisciplinary education combining topics such as advanced machine learning algorithms, statistical principles that provide the foundations for these algorithms, database and data warehousing methods, complexity analysis, approaches to data visualization, privacy and security issues, and specific application areas such as business, marketing, and public policy.