Dean Abbott is the President of Abbott Analytics, Inc. in San Diego, California. He has
over two decades experience in applying advanced data mining, data preparation, and
data visualization methods in real-world data intensive problems, including fraud detection,
customer acquisition and retention, digital behavior for web applications and mobile,
customer lifetime value, survey analysis, donation solicitation and planned giving. He has
developed, coded, and evaluated algorithms for use in commercial data mining and pattern
recognition products, including polynomial networks, neural networks, radial basis functions,
and clustering algorithms for multiple software vendors.
He is a seasoned instructor, having taught a wide range of data mining tutorials and
seminars to thousands of attendees, including PAW, KDD, INFORMS, DAMA, AAAI, and IEEE
conferences. He is the instructor of well-regarded data mining courses, explaining concepts
in language readily understood by a wide range of audiences, including analytics novices,
data analysts, statisticians, and business professionals. He also has taught both applied
and hands-on data mining courses for major software vendors, including IBM SPSS Modeler,
Statsoft STATISTICA, Salford System SPM, SAS Enterprise Miner, IBM PredictiveInsight, Tibco
Spotfi re Miner, KNIME, RapidMiner, and Megaputer Polyanalyst.
