Abstract
The past two decades has seen a huge wave of computational systems for the “digitization” of business operations from ERP, to manufacturing, to systems for customer interactions. These systems increased the throughput and efficiency of conducting “transactions” and resulted in an unprecedented build-up of data captured from these systems. The paradoxical reality that most organizations face today is that they have more data about every aspect of their operations and customers, yet they find themselves with an ever diminishing understanding of either. Data Mining has received much attention as a technology that can possibly bridge the gap between data and knowledge.
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© 2004 Springer-Verlag Berlin Heidelberg
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Fayyad, U. (2004). Data Mining Grand Challenges. In: Dai, H., Srikant, R., Zhang, C. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2004. Lecture Notes in Computer Science(), vol 3056. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24775-3_2
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DOI: https://doi.org/10.1007/978-3-540-24775-3_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22064-0
Online ISBN: 978-3-540-24775-3
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