Data mining for managers : how to use data (big and small) to solve business challenges / Richard Boire.
Publisher: New York, NY : Palgrave Macmillan, ©2016Description: xii, 242 pages ; 25 cmContent type:- text
- unmediated
- volume
- 9781349487868 (alk. paper)
- HD30.2 .B6373 2016
BOOKS
| Current library | Home library | Call number | Status | Barcode | |
|---|---|---|---|---|---|
| Alfaisal University On Shelf | Alfaisal University On Shelf | HD30.2 .B6373 2016 (Browse shelf(Opens below)) | Available | AU00000000011787 |
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| HD30.19 .M22 2014 The moment of clarity : | HD30.2 .A34 2026 AI in business for dummies | HD30.2 .B54 2018 Big data demystified how to use big data, data science and AI to make better business decisions and gain competitive advantage | HD30.2 .B6373 2016 Data mining for managers : | HD30.2 .B64 1999 Knowledge assets : | HD30.2 .B73 2018 The future of tech is female : | HD30.2 .D543 2022 Digital transformation and institutional theory / |
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.

