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Book Cover
Book
Author Sharda, Ramesh.

Title Business intelligence : a managerial perspective on analytics / Ramesh Sharda, Oklahoma State University, Dursun Delen, Oklahoma State University, Efraim Turban, University of Hawaii ; with contributions by J. E. Aronson, The University of Georgia, Ting-Peng Liang, National Sun Yat-sen University, David King, JDA Software Group, Inc
Edition Third edition
Published Boston Pearson, [2014]

Copies

Location Call no. Vol. Availability
 W'BOOL  658.472 Sha/Bia 2014  AVAILABLE
 W'BOOL  658.472 Sha/Bia 2014  AVAILABLE
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 MELB  658.472 Sha/Bia 2014  AVAILABLE
 MELB  658.472 Sha/Bia 2014  AVAILABLE
 MELB  658.472 Sha/Bia 2014  AVAILABLE
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 WATERFT BUSINESS  658.472 Sha/Bia 2014  AVAILABLE
Description 386 pages : illustrations ; 26 cm
Contents Contents note continued: 2.5.Data Integration and the Extraction, Transformation, and Load (ETL) Processes -- Data Integration -- Application Case 2.3 BP Lubricants Achieves BIGS Success -- Extraction, Transformation, and Load -- 2.6.Data Warehouse Development -- Application Case 2.4 Things Go Better with Coke's Data Warehouse -- Data Warehouse Development Approaches -- Application Case 2.5 Starwood Hotels & Resorts Manages Hotel Profitability with Data Warehousing -- Additional Data Warehouse Development Considerations -- Representation of Data in Data Warehouse -- Analysis of Data in Data Warehouse -- OLAP Versus OLTP -- OLAP Operations -- 2.7.Data Warehousing Implementation Issues -- Application Case 2.6 EDW Helps Connect State Agencies in Michigan -- Massive Data Warehouses and Scalability -- 2.8.Real-Time Data Warehousing -- Application Case 2.7 Egg Plc Fries the Competition in Near Real Time -- 2.9.Data Warehouse Administration, Security Issues, and Future Trends --
Contents note continued: 4.2.Data Mining Concepts and Applications -- Definitions, Characteristics, and Benefits -- Application Case 4.1 Smarter Insurance: Infinity P&C Improves Customer Service and Combats Fraud with Predictive Analytics -- How Data Mining Works -- Application Case 4.2 Harnessing Analytics to Combat Crime: Predictive Analytics Helps Memphis Police Department Pinpoint Crime and Focus Police Resources -- Data Mining Versus Statistics -- 4.3.Data Mining Applications -- Application Case 4.3 A Mine on Terrorist-Funding -- 4.4.Data Mining Process -- Step 1: Business Understanding -- Step 2: Data Understanding -- Step 3: Data Preparation -- Step 4: Model Building -- Step 5: Testing and Evaluation -- Step 6: Deployment -- Application Case 4.4 Data Mining in Cancer Research -- Other Data Mining Standardized Processes and Methodologies -- 4.5.Data Mining Methods -- Classification -- Estimating the True Accuracy of Classification Models --
Contents note continued: 7.7.Impacts of Analytics In Organizations: An Overview -- New Organizational Units -- Restructuring Business Processes and Virtual Teams -- Job Satisfaction -- Job Stress and Anxiety -- Analytics' Impact on Managers' Activities and Their Performance -- 7.8.Issues of Legality, Privacy, and Ethics -- Legal Issues -- Privacy -- Recent Technology Issues in Privacy and Analytics -- Ethics in Decision Making and Support -- 7.9.An Overview of the Analytics Ecosystem -- Analytics Industry Clusters -- Data Infrastructure Providers -- Data Warehouse Industry -- Middleware/BI Platform Industry -- Data Aggregators/Distributors -- Analytics-Focused Software Developers -- Reporting/Analytics -- Predictive Analytics -- Prescriptive Analytics -- Application Developers or System Integrators: Industry Specific or General -- Analytics User Organizations -- Analytics Industry Analysis and Influencers -- Academic Providers and Certification Agencies -- Key Terms --
Contents note continued: Application Case 3.4 TIBCO Spotfire Trovides Dana-Farber Cancer Institute with Unprecedented Insight into Cancer Vaccine Clinical Trials -- 3.4.Different Types of Charts and Graphs -- Basic Charts and Graphs -- Specialized Charts and Graphs -- 3.5.The Emergence of Data Visualization and Visual Analytics -- Visual Analytics -- High-Powered Visual Analytics Environments -- 3.6.Performance Dashboards -- Dashboard Design -- Application Case 3.5 Dallas Cowboys Score Big with Tableau and Teknion -- Application Case 3.6 Saudi Telecom Company Excels with Information Visualisation -- What to Look For in a Dashboard -- Best Practices in Dashboard Design -- Benchmark Key Performance Indicators with Industry Standards -- Wrap the Dashboard Metrics with Contextual Metadata -- Validate the Dashboard Design by a Usability Specialist -- Prioritize and Rank Alerts/Exceptions Streamed to the Dashboard -- Enrich Dashboard with Business-User Comments --
Contents note continued: Application Case 4.5 2degrees Gets a 1275 Percent Boost in Churn Identification -- Cluster Analysis for Data Mining -- Association Rule Mining -- 4.6.Data Mining Software Tools -- Application Case 4.6 Data Mining Goes to Hollywood: Predicting Financial Success of Movies -- 4.7.Data Mining Privacy Issues, Myths, and Blunders -- Data Mining and Privacy Issues -- Application Case 4.7 Predicting Customer Buying Patterns The Target Story -- Data Mining Myths and Blunders -- Key Terms -- Questions for Discussion -- Exercises -- End-of-Chapter Application Case -- References -- 5.1.Opening Vignette: Machine Versus Men on Jeopardy!: The Story of Watson -- 5.2.Text Analytics and Text Mining Overview -- Application Case 5.1 Text Mining for Patent Analysis -- 5.3.Natural Language Processing -- Application Case 5.2 Text Mining Improves Hong Kong Government's Ability to Anticipate and Address Public Complaints -- 5.4.Text Mining Applications --
Contents note continued: Application Case 6.4 Big Data and Analytics in Politics -- 6.6.Big Data and Data Warehousing -- Use Cases for Hadoop -- Use Cases for Data Warehousing -- The Gray Areas (Any One of the Two Would Do the Job) -- Coexistence of Hadoop and Data Warehouse -- 6.7.Big Data Vendors -- Application Case 6.5 Dublin City Council Is Leveraging Big Data to Reduce Traffic Congestion -- Application Case 6.6 Creditreform Boosts Credit Rating Quality with Big Data Visual Analytics -- 6.8.Big Data And Stream Analytics -- Stream Analytics Versus Perpetual Analytics -- Critical Event Processing -- Data Stream Mining -- 6.9.Applications of Stream Analytics -- e-Commerce -- Telecommunications -- Application Case 6.7 Turning Machine-Generated Streaming Data into Valuable Business Insights -- Law Enforcement and Cyber Security -- Power Industry -- Financial Services -- Health Sciences -- Government -- Key Terms -- Questions for Discussion -- Exercises --
Contents note continued: Development Cycle -- Web Crawler -- Document Indexer -- Response Cycle -- Query Analyzer -- Document Matcher/Ranker -- Search Engine Optimization -- Methods for Search Engine Optimization -- Application Case 5.7 Understanding Why Customers Abandon Shopping Carts Results in a $10 Million Sales Increase -- 5.9.Web Usage Mining (Web Analytics) -- Web Analytics Technologies -- Application Case 5.8 Allegro Boosts Online Click-Through Rates by 500 Percent with Web Analysis -- Web Analytics Metrics -- Web Site Usability -- Traffic Sources -- Visitor Profiles -- Conversion Statistics -- 5.10.Social Analytics -- Social Network Analysis -- Social Network Analysis Metrics -- Application Case 5.9 Social Network Analysis Helps Telecommunication Firms -- Connections -- Distributions -- Segmentation -- Social Media Analytics -- How Do People Use Social Media? -- Application Case 5.10 Measuring the Impact of Social Media at Lollapalooza --
Contents note continued: End-of-Chapter Application Case -- References -- 7.1.Opening Vignette: Oklahoma Gas and Electric Employs Analytics to Promote Smart Energy Use -- 7.2.Location-Based Analytics for Organizations -- Geospatial Analytics -- Application Case 7.1 Great Clips Employs Spatial Analytics to Shave Time in Location Decisions -- Real-Time Location Intelligence -- Application Case 7.2 Quiznos Targets Customers for its Sandwiches -- 7.3.Analytics Applications for Consumers -- Application Case 7.3 A Life Coach in Your Pocket -- 7.4.Recommendation Engines -- 7.5.The Web 2.0 Revolution and Online Social Networking -- Representative Characteristics of Web 2.0 -- Social Networking -- A Definition and Basic Information -- Implications of Business and Enterprise Social Networks -- 7.6.Cloud Computing and BI -- Service-Oriented DSS -- Data-as-a-Service (DaaS) -- Information-as-a-Service (Information on Demand) (IaaS) -- Analytics-as-a-Service (AaaS) --
Contents note continued: Justification and Cost-Benefit Analysis -- Security and Protection of Privacy -- Integration of Systems and Applications -- 1.7.Analytics Overview -- Descriptive Analytics -- Predictive Analytics -- Application Case 1.2 Eliminating Inefficiencies at Seattle Children's Hospital -- Application Case 1.3 Analysis at the Speed of Thought -- Prescriptive Analytics -- Application Case 1.4 Moneyball: Analytics in Sports and Movies -- Application Case 1.5 Analyzing Athletic Injuries -- Analytics Applied to Different Domains -- Application Case 1.6 Industrial and Commercial Bank of China (ICBC) Employs Models to Reconfigure Its Branch Network -- Analytics or Data Science? -- 1.8.Brief Introduction to Big Data Analytics -- What Is Big Data? -- Application Case 1.7 Gilt Groupe's Flash Sales Streamlined by Big Data Analytics -- 1.9.Plan of the Book -- 1.10.Resources, Links, and the Teradata University Network Connection -- Resources and Links --
Contents note continued: Marketing Applications -- Security Applications -- Application Case 5.3 Mining for Lies -- Biomedical Applications -- Academic Applications -- Application Case 5.4 Text mining and Sentiment Analysis Help Improve Customer Service Performance -- 5.5.Text Mining Process -- Task 1: Establish the Corpus -- Task 2: Create the Term-Document Matrix -- Task 3: Extract the Knowledge -- Application Case 5.5 Research Literature Survey with Text Mining -- 5.6.Sentiment Analysis -- Application Case 5.6 Whirlpool Achieves Customer Loyalty and Product Success with Text Analytics -- Sentiment Analysis Applications -- Sentiment Analysis Process -- Methods for Polarity Identification -- Using a Lexicon -- Using a Collection of Training Documents -- Identifying Semantic Orientation of Sentences and Phrases -- Identifying Semantic Orientation of Document -- 5.7.Web Mining Overview -- Web Content and Web Structure Mining -- 5.8.Search Engines -- Anatomy of a Search Engine --
Contents note continued: Measuring the Social Media Impact -- Best Practices in Social Media Analytics -- Application Case 5.11 eHarmony Uses Social Media to Help Take the Mystery Out of Online Dating -- Key Terms -- Questions for Discussion -- Exercises -- End-of-Chapter Application Case -- References -- 6.1.Opening Vignette: Big Data Meets Big Science at CERN -- 6.2.Definition of Big Data -- The Vs That Define Big Data -- Application Case 6.1 BigData Analytics Helps Luxottica Improvement its Marketing Effectiveness -- 6.3.Fundamentals of Big Data Analytics -- Business Problems Addressed by Big Data Analytics -- Application Case 6.2 Top 5 Investment Bank Achieves Single Source of the Truth -- 6.4.Big Data Technologies -- MapReduce -- Why Use MapReduce? -- Hadoop -- How Does Hadoop Work? -- Hadoop Technical Components -- Hadoop: The Pros and Cons -- NoSQL -- Application Case 6.3 eBay's Big Data Solution -- 6.5.Data Scientist -- Where Do Data Scientists Come From? --
Contents note continued: Present Information in Three Differenttevels -- Pick the Right Visual Construct Using Dashboard Design Principles -- Provide for Guided Analytics -- 3.7.Business Performance Management -- Closed-Loop BPM Cycle -- Application Case 3.7 IBM Cognos Express Helps Mace for Faster and Better Business Reporting -- 3.8.Performance Measurement -- Key Performance Indicator (KPI) -- Performance Measurement System -- 3.9.Balanced Scorecards -- The Four Perspectives -- The Meaning of Balance in BSC -- Dashboards Versus Scorecards -- 3.10.Six Sigma as a Performance Measurement System -- The DMAIC Performance Model -- Balanced Scorecard Versus Six Sigma -- Effective Performance Measurement -- Application Case 3.8 Expedia.com's Customer Satisfaction Scorecard -- Key Terms -- Questions for Discussion -- Exercises -- End-of-Chapter Application Case -- References -- 4.1.Opening Vignette: Cabela's Reels in More Customers with Advanced Analytics and Data Mining --
Contents note continued: Questions for Discussion -- Exercises -- End-of-Chapters Application Case -- References
Contents note continued: The Future of Data Warehousing -- 2.10.Resources, Links, and the Teradata University Network Connection -- Resources and Links -- Cases -- Vendors, Products, and Demos -- Periodicals -- Additional References -- The Teradata University Network (TUN) Connection -- Key Terms -- Questions for Discussion -- Exercises -- End-of-Chapter Application Case -- References -- 3.1.Opening Vignette: Self-Service Reporting Environment Saves Millions for Corporate Customers -- 3.2.Business Reporting Definitions and Concepts -- What Is a Business Report? -- Application Case 3.1 Delta Lloyd Group Ensures Accuracy and Efficiency in Financial Reporting -- Components of Business Reporting Systems -- Application Case 3.2 Flood of Paper Ends at FEMA -- 3.3.Data and Information Visualization -- Application Case 3.3 Tableau Saves Blastrac Thousands of Dollars with Simplified Information Sharing -- A Brief History of Data Visualization --
Contents note continued: Vendors, Products, and Demos -- Periodicals -- The Teradata University Network Connection -- The Book's Web Site -- Key Terms -- Questions for Discussion -- Exercises -- End-of-Chapter Application Case -- References -- 2.1.Opening Vignette: Isle of Capri Casinos Is Winning with Enterprise Data Warehouse -- 2.2.Data Warehousing Definitions and Concepts -- What Is a Data Warehouse? -- A Historical Perspective to Data Warehousing -- Characteristics of Data Warehousing -- Data Marts -- Operational Data Stores -- Enterprise Data Warehouses (EDW) -- Application Case 2.1 A Better Data Plan: Well-Established TELCOs Leverage Data Warehousing and Analytics to Stay on Top in a Competitive Industry -- Metadata -- 2.3.Data Warehousing Process Overview -- Application Case 2.2 Data Warehousing Helps MultiCare Save More Lives -- 2.4.Data Warehousing Architectures -- Alternative Data Warehousing Architectures -- Which Architecture Is the Best? --
Machine generated contents note: 1.1.Opening Vignette: Magpie Sensing Employs Analytics to Manage a Vaccine Supply Chain Effectively and Safely -- 1.2.Changing Business Environments and Computerized Decision Support -- The Business Pressures-Responses-Support Model -- 1.3.A Framework for Business Intelligence (BI) -- Definitions of BI -- A Brief History of BI -- The Architecture of BI -- The Origins and Drivers of BI -- Application Case 1.1 Sabre Helps Its Clients Through Dashboards and Analytics -- A Multimedia Exercise in Business Intelligence -- 1.4.Intelligence Creation, Use, and BI Governance -- A Cyclical Process of Intelligence Creation and Use -- Intelligence and Espionage -- 1.5.Transaction Processing Versus Analytic Processing -- 1.6.Successful BI Implementation -- The Typical BI User Community -- Appropriate Planning and Alignment with the Business Strategy -- Real-Time, On-Demand BI Is Attainable -- Developing or Acquiring BI Systems --
Summary This book is for courses on Business Intelligence or Decision Support Systems. It gives a managerial approach to understanding business intelligence systems. To help future managers use and understand analytics, this text provides students with a solid foundation of Business Intelligence that is reinforced with hands-on practice
Notes Includes bibliographical references and index
Bibliography Includes bibliographical references and index
Subject Business intelligence.
Industrial management.
Management.
Author Delen, Dursun, author
Turban, Efraim, author
LC no. 2013030282
ISBN 0133051056
9780133051056