Abstract

Data mining remains an important research area in database systems and a major challenge in computer science. We present a review of processing alternatives, storage mechanisms, algorithms, data structures and optimizations that enable data mining on large data sets. We focus on the computation of well-known multidimensional statistical and machine learning models. We pay particular attention to SQL (together with UDFs) and MapReduce as two competing technologies for large scale processing, especially with parallel computing. We conclude with a summary of solved major problems and open research issues.

Integrating Database Systems and Data Mining Algorithms (Guest Speaker Professor Carlos Ordonez, University of Houston)