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Data mining for managers : how to use data (big and small) to solve business challenges / Richard Boire.

By: Boire, Richard.
Publisher: New York, NY : Palgrave Macmillan, ©2016Description: xii, 242 pages ; 25 cm.Content type: text Media type: unmediated Carrier type: volumeISBN: 9781349487868 (alk. paper).Subject(s): Management -- Computer programs | Data miningGenre/Form: Print books.
Contents:
Introduction -- Growth of data mining and the data miner -- Data mining in the new economy -- Using data mining for crm evaluation -- The data mining process-problem identification -- The data mining process - creation of the analytical file -- Data mining process-creation of the analytical file : using external data sources -- Data storage and security -- Privacy concerns regarding the use of data -- Types and quality of data -- Segmentation -- Applying data mining techniques -- Gains charts -- Using rfm as one targeting option -- The use of multivariate analysis techniques -- Tracking and measuring -- Implementation and tracking -- Value-based segmentation and the use of chaid -- Black box analytics -- Digital analytics : a data miner's perspective -- Organizational considerations/people and software -- Social media analytics -- Credit cards and risk -- Data mining in retail -- Business to business example -- Financial institution case study -- Using marketing analytics in the travel/entertainment industry -- Data mining for customer loyalty : a perspective -- Text mining : the new data mining frontier -- Analytics and data mining for insurance claim risk -- Future thoughts : the big data discussion and the key roles within analytics.
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Introduction -- Growth of data mining and the data miner -- Data mining in the new economy -- Using data mining for crm evaluation -- The data mining process-problem identification -- The data mining process - creation of the analytical file -- Data mining process-creation of the analytical file : using external data sources -- Data storage and security -- Privacy concerns regarding the use of data -- Types and quality of data -- Segmentation -- Applying data mining techniques -- Gains charts -- Using rfm as one targeting option -- The use of multivariate analysis techniques -- Tracking and measuring -- Implementation and tracking -- Value-based segmentation and the use of chaid -- Black box analytics -- Digital analytics : a data miner's perspective -- Organizational considerations/people and software -- Social media analytics -- Credit cards and risk -- Data mining in retail -- Business to business example -- Financial institution case study -- Using marketing analytics in the travel/entertainment industry -- Data mining for customer loyalty : a perspective -- Text mining : the new data mining frontier -- Analytics and data mining for insurance claim risk -- Future thoughts : the big data discussion and the key roles within analytics.

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