MARC Record from marc_nuls

LEADER: 06357pam 22003494a 4500
001 9920610880001661
005 20150423130823.0
008 001127s2001 paua b 001 0 eng
010 $a 00054107
020 $a1930708033
035 $a(CSdNU)u95244-01national_inst
035 $a(Sirsi) l00054107
035 $a(Sirsi) l00054107
035 $a(Sirsi) 01-AAL-6661
035 $a 00054107
040 $aDLC$cDLC$dNhCcYBP$dOrPss
042 $apcc
050 00 $aHF 5548.2$bK766 2001
100 1 $aKudyba, Stephan,$d1963-
245 10 $aData mining and business intelligence :$ba guide to productivity / $cStephan Kudyba, Richard Hoptroff.
260 $aHershey [Pa.] :$bIdea Group Pub.,$cc2001.
300 $aiv, 166 p. :$bill. ;$c26 cm.
504 $aIncludes bibliographical references and index.
505 0 $aLaying the Groundwork for Data Mining Technology -- An Introduction to Information Technology and Business Intelligence -- A Driving Source of Productivity (IT, Economic Theory and Business Strategy) -- An Introduction to Business Intelligence -- The BI Spectrum: Data Extraction and Report Writing, OLAP, Internets, Extranets and the Internet -- Business Intelligence Extended (An Introduction to Data Mining) -- An Introduction to Data Mining Methodologies -- Visualization Tools for Reporting and Monitoring: The Humble Chart -- The Business Intelligence Cycle -- Using Mining to Extend OLAP -- Closing Thoughts on Business Intelligence and Productivity -- Reducing Uncertainty by Minimizing the Variance -- Data Mining Defined -- The Roots of Data Mining -- A Closer Look at the Mining Process: (The Traditional Method) -- Segmentation and Classification Revisited -- Neural Network and Regression Mining (The Robust Approach) -- A Brief History of Neural Networks -- Back to Regression and Neural Nets -- How Mining Differs from the Traditional Approach (A Focus on Neural Nets and Regression) -- Summing up the Definition of Data Mining -- A Broad Overview of Data Mining Technologies -- Steps To Success for the Mining Process -- Mining the Right Data (Garbage In, Garbage Out) -- How Much Is My Existing Data Worth? -- Think First, Mine Later (Nine Easy Steps for Success) -- Pitfalls: Torturing the Data to Get the Answer You Want to Hear -- Pitfall: The Pursuit of Statistical Perfection -- Bridging the Steps to Success to 6 Sigma Applications (Productivity Enhancing Strategies) -- Essential Mining Approaches to Problem Solving -- Forecasting Tools -- Forecasting: Univariate and Multivariate -- From Analysis Over Time to Analysis of a Snapshot in Time -- Target Measures and Probability Mining -- Prevalent Applications in the World of Commerce -- A Closer Look at Marketing/Advertising, Promotions and Pricing Policies Using Econometric Based Modeling -- Regression/Neural Networks for Marketing Analysis -- Measuring the Immediate Impact of Advertising -- Measuring the Impact of Price and Promotions -- Measuring the Longer Term Impact of Advertising -- Other Techniques to Measure Longer Term Impacts of Advertising on Target Measures -- A Closer Look at Pricing Strategies -- Price Optimization Using Cross-Sections: Data Mining for Pricing -- Price Elasticity -- Finding the Optimum and Break-Even Prices -- A Brief Mention of Other Regression and Neural Network Applications -- Market Research Analysis -- Personnel Performance and Retention (HR) -- Personnel Selection -- Retail Outlet Location Analysis -- Business Unit Analysis -- Closing Thoughts -- Turning Your Brick and Mortar into a Click and Mortar by Engage Inc. -- The Establishment Goes Wired -- Online Profiling is the Key -- The 360 Degree Customer View -- Modify and Convert -- A Word on Privacy -- To Infinity...And Beyond -- Did You Ever Think Your Data Would Be This Valuable? -- Improving the Web Experience through Real-Time Analysis (A Market Basket Approach) by Macromedia -- An Introduction to Internet Personalization -- Basic Personalization -- Collaborative Filtering Brings New Dimension of Pattern Recognition to Personalization -- Item Affinity: An Extension to Traditional Market Basket Analysis -- One Advantage of Market Basket Analysis Over Item Affinity -- Item Affinity: Taking the Best of Market Basket Theory to the Internet -- How an Implementation of Item Affinity Works in Comparison to Market Basket Analysis -- A Recap of Why Item Affinity is Superior to Market Basket Analysis for Online Marketing -- Feature Comparisons of Market Basket Analysis and an Implementation of Real-Time Item Affinity -- A More Detailed Description of Item Affinity -- Counting Basics--How Item Affinity Goes About Its Tasks -- Multiple Baskets: Telling Item Affinity How to Count By Compressing Time -- Multiple Events: Telling Item Affinity What to Count by Expanding Events -- Item Affinity in the Real World -- Bringing It All Together (Data Mining on an Enterprise Level) -- The Gap Problems (Communication and Knowledge) -- Steps to Achieving a Total Solution with Mining -- One Model Rarely Captures an Entire Business Solution: A Human Resource Application -- Model Optimization and an Introduction to Variance -- CRM Revisited -- Other Factors that Promote a Dynamic Business Environment -- The Changing Structure of the Economy and Macro Model Optimization -- Feedback from Functional Areas -- The Data Mining Solution within the BI Spectrum and Integration with Other IT Components -- Using IT to Survive in the Information Age -- What the Future Holds for Data Mining -- A Quick Word on Innovations in Algorithms -- The Evolution of E-Business and New Data Mining -- User Friendly Mining Reports -- Regression and Neural Network Reports -- CRM One More Time -- Continued Streamlining or Simplification of the Data Access and Extraction Process for Mining -- Enhancements in Data Storage Techniques (Warehouses and Marts) -- Closing the Gap (The Evolution of the Workforce and Data Mining Technology).
650 0 $aBusiness$xComputer network resources.
650 0 $aBusiness$xData processing.
650 0 $aOffice information systems.
650 0 $aManagement information systems.
650 0 $aElectronic commerce.
700 1 $aHoptroff, Richard.
948 $a06/25/2001$b07/24/2001
999 $aHF 5548.2 K766 2001$wLC$c1$i31786101481254$d4/9/2013$e9/15/2011 $f3/22/2004$g1$lCIRCSTACKS$mNULS$n2$q1$rY$sY$tBOOK$u7/24/2001