A Stand-alone Methodology for Data Exploration: in Support of Data Mining and Analytics - Michael Gage - Books - LAP LAMBERT Academic Publishing - 9783659464119 - October 31, 2013
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A Stand-alone Methodology for Data Exploration: in Support of Data Mining and Analytics

Michael Gage

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A Stand-alone Methodology for Data Exploration: in Support of Data Mining and Analytics

With the emergence of Big Data, data high in volume, variety, and velocity, new analysis techniques need to be developed to effectively use the data that is being collected. Knowledge discovery from databases is a larger methodology encompassing a process for gathering knowledge from that data. Analytics pair the knowledge with decision making to improve overall outcomes. Organizations have conclusive evidence that analytics provide competitive advantages and improve overall performance. This paper proposes a stand-alone methodology for data exploration. Data exploration is one part of the data mining process, used in knowledge discovery from databases and analytics. The goal of the methodology is to reduce the amount of time to gain meaningful information about a previously unanalyzed data set using tabular summaries and visualizations. The reduced time will enable faster implementation of analytics in an organization. Two case studies using a prototype implementation are presented showing the benefits of the methodology.

Media Books     Paperback Book   (Book with soft cover and glued back)
Released October 31, 2013
ISBN13 9783659464119
Publishers LAP LAMBERT Academic Publishing
Pages 116
Dimensions 150 × 7 × 225 mm   ·   191 g
Language German