| Foreword |
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xi | |
| Introduction |
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xiii | |
| What Is the Scope of Business Analytics? Information Systems---Not Technical Solutions |
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xvii | |
| Purpose and Audience |
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xix | |
Organization of Chapters |
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xxiii | |
| Why the Term Business Analytics? |
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xxiv | |
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Chapter 1 The Business Analytics Model |
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1 | (16) |
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Overview of the Business Analytics Model |
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2 | (4) |
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4 | (1) |
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Business Processes and Information Use |
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4 | (1) |
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Types of Reporting and Analytical Processes |
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5 | (1) |
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5 | (1) |
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Data Sources: IT Operations and Development |
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5 | (1) |
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Deployment of the Business Analytics Model |
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6 | (7) |
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Case Study: How to Make an Information Strategy for a Radio Station |
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6 | (7) |
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13 | (4) |
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Chapter 2 Business Analytics at the Strategic Level |
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17 | (30) |
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Link between Strategy and the Deployment of Business Analytics |
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19 | (1) |
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Strategy and Business Analytics: Four Scenarios |
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20 | (12) |
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Scenario 1 No Formal Link between Strategy and Business Analytics |
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22 | (2) |
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Scenario 2 Business Analytics Supports Strategy at a Functional Level |
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24 | (4) |
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Scenario 3 Dialogue between the Strategy and the Business Analytics Functions |
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28 | (2) |
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Scenario 4 Information as a Strategic Resource |
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30 | (2) |
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Which Information Do We Prioritize? |
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32 | (12) |
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The Product and Innovation Perspective |
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34 | (4) |
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Customer Relations Perspective |
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38 | (4) |
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The Operational Excellence Perspective |
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42 | (2) |
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44 | (3) |
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Chapter 3 Development and Deployment of information at the Functional Level |
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47 | (56) |
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Case Study: A Trip to the Summerhouse |
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50 | (9) |
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Specification of Requirements |
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51 | (1) |
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52 | (1) |
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Off We Go to the Summerhouse |
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53 | (1) |
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54 | (3) |
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More about Lead and Lag Information |
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57 | (2) |
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Establishing Business Processes with the Rockart Model |
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59 | (2) |
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Example: Establishing New Business Processes with the Rockart Model |
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61 | (11) |
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Level 1 Identifying the Objectives |
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62 | (1) |
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Level 2 Identifying an Operational Strategy |
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62 | (2) |
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Level 3 Identifying the Critical Success Factors |
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64 | (2) |
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Level 4 Identifying Lead and Lag Information |
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66 | (6) |
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Optimizing Existing Business Processes |
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72 | (1) |
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Example: Deploying Performance Management to Optimize Existing Processes |
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73 | (5) |
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Concept of Performance Management |
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74 | (4) |
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Which Process Should We Start With? |
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78 | (21) |
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Customer Relationship Management Activities |
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80 | (4) |
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84 | (1) |
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85 | (1) |
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86 | (3) |
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89 | (2) |
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Human Resource Development |
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91 | (2) |
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Corporate Performance Management |
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93 | (1) |
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94 | (1) |
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95 | (1) |
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95 | (2) |
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97 | (2) |
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A Catalogue of Ideas with Key Performance Indicators for the Company's Different Functions |
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99 | (2) |
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101 | (2) |
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Chapter 4 Business Analytics at the Analytical Level |
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103 | (46) |
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Data, Information, and Knowledge |
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106 | (1) |
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Analyst's Role in the Business Analytics Model |
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107 | (2) |
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Three Requirements the Analyst Must Meet |
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109 | (4) |
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110 | (1) |
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Tool Kit Must Be in Order (Method Competencies) |
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111 | (1) |
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Technical Understanding (Data Competencies) |
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112 | (1) |
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Required Competencies for the Analyst |
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113 | (16) |
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Analytical Methods (Information Domains) |
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113 | (1) |
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How to Select the Analytical Method |
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114 | (2) |
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116 | (6) |
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Descriptive Statistical Methods, Lists, and Reports |
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122 | (7) |
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Hypothesis-Driven Methods |
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129 | (4) |
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Tests with Several Input Variables |
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130 | (3) |
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Data Mining with Target Variables |
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133 | (7) |
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139 | (1) |
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140 | (3) |
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141 | (1) |
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141 | (1) |
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142 | (1) |
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143 | (1) |
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143 | (4) |
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Definition of the Overall Problem |
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144 | (1) |
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144 | (1) |
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145 | (2) |
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147 | (2) |
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Chapter 5 Business Analytics at the Data Warehouse Level |
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149 | (36) |
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151 | (3) |
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Architecture and Processes in a Data Warehouse |
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154 | (21) |
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Selection of Certain Columns To Be Loaded |
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156 | (2) |
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Staging Area and Operational Data Stores |
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158 | (1) |
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Causes and Effects of Poor Data Quality |
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159 | (3) |
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The Data Warehouse: Functions, Components, and Examples |
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162 | (8) |
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Alternative Ways of Storing Data |
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170 | (1) |
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Business Analytics Portal: Functions and Examples |
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171 | (4) |
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Tips and Techniques in Data Warehousing |
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175 | (8) |
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175 | (1) |
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Service-Oriented Architecture |
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176 | (1) |
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How Should Data Be Accessed? |
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177 | (1) |
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Access to Business Analytics Portals |
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178 | (2) |
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Access to Data Mart Areas |
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180 | (1) |
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Access to Data Warehouse Areas |
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181 | (1) |
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182 | (1) |
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183 | (2) |
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Chapter 6 The Company's Collection of Source Data |
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185 | (14) |
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What Are Source Systems, and What Can They Be Used For? |
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187 | (5) |
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Which Information Is Best to Use for Which Task? |
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192 | (2) |
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When There Is More Than One Way to Get the Job Done |
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194 | (3) |
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When the Quality of Source Data Fails |
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197 | (1) |
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198 | (1) |
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Chapter 7 Structuring of a Business Analytics Competency Center |
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199 | (22) |
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What Is a Business Analytics Competency Center? |
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201 | (1) |
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Why Set Up a Business Analytics Competency Center? |
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202 | (1) |
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203 | (5) |
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Establishing an Information Wheel |
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203 | (2) |
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Creating Synergies between Information Wheels |
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205 | (2) |
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207 | (1) |
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Prioritizing New Business Analytics Initiatives |
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208 | (1) |
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208 | (5) |
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Centralized or Decentralized Organization |
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208 | (2) |
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210 | (3) |
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When the Analysts Report to the IT Department |
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213 | (2) |
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When Should a Business Analytics Competency Center Be Established? |
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215 | (2) |
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Applying the Analytical Factory Approach |
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217 | (2) |
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219 | (2) |
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Chapter 8 Assessment and Prioritization of Business Analytics Projects |
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221 | (26) |
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Is It a Strategic Project or Not? |
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222 | (8) |
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Uncovering the Value Creation of the Project |
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224 | (6) |
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When Projects Run Over Several Years |
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230 | (2) |
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When the Uncertainty Is Too Big |
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232 | (3) |
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The Descriptive Part of the Cost/Benefit Analysis for the Business Case |
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233 | (2) |
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The Cost/Benefit Analysis Used for the Business Case |
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235 | (1) |
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Projects as Part of the Bigger Picture |
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235 | (8) |
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Case Study on How to Make an Information Strategy Roadmap |
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240 | (3) |
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243 | (4) |
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Chapter 9 Business Analytics in the Future |
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247 | (8) |
| About the Authors |
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255 | (2) |
| Index |
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257 | |