Business Intelligence for Small and Medium-Sized Enterprises : an Agile Roadmap Toward Business Sustainability.

Cover; Half Title; Title Page; Copyright Page; Dedication; CONTENTS; FOREWORD; AUTHORS; INTRODUCTION: CONCEPTIONS OF AGILITY AND BUSINESS INTELLIGENCE FOR SMES; Digital Business Trends; Conceptions of Agility; Business Intelligence as an Enabler of Agility; SMEs, Business Intelligence and Agility; About this Book; PART I: BI LANDSCAPE -- OPPORTUNITIES FOR SMEs; CHAPTER 1 BARRIERS AND STRATEGIES FOR ENTERPRISE ICT ADOPTION IN SMES; Introduction (Digital Economy -- Implications for Business); SMEs and ICT in Developing Economies; SMEs and ICT Adoption -- Barriers & Challenges

BI -- Value Opportunities for SMEsDistribution and Retail; Credit and Micro-Finance Services; CHAPTER 2 AN AGILE INTEGRATED METHODOLOGY FOR STRATEGIC BUSINESS INTELLIGENCE (AIMS-BI); Introduction; Why the Need for New Methodologies?; The Need for a Strategic, yet Agile Perspective; Know the Current State of your Information Maturity; End User and Key Stakeholder Engagement; Design of AIMS-BI; Description of AIMS-BI; Step 1: Information Maturity Assessment; Step 2: BI Opportunity Discovery; Step 3: BI Portfolio Evaluation; Step 4: Proof of Concept Prototypes

Strategic Business Intelligence RoadmapFindings from Applying AIMS-BI; Conclusion; PART II: NAVIGATING THE AGILE BI PROCESS; CHAPTER 3 INFORMATION MANAGEMENT (IM) MATURITY ASSESSMENT: EVALUATING BUSINESS CAPABILITIES AND GAPS; Introduction; Maturity Models in Organizations; Implementing the IM Maturity Model; Applying the AIMS-BI IM Maturity Assessment; Example of the Application of IM Maturity Assessment; Conclusion; CHAPTER 4 CREATING BI PORTFOLIOS; Introduction; The Discovery of BI Opportunities; BI Portfolio Evaluation; Example: BI Opportunity Discovery and Portfolio Evaluation

ConclusionCHAPTER 5 THE PROCESS AND VALUE OF BUILDING PROOF-OF-CONCEPT PROTOTYPES; Introduction; Why Develop PoCs?; BI -- The Different Layers of Analytics; Monitoring Layer; What Is Data Visualization?; Data Visualization Process Models (VPM); Understanding the Business Context; Get Data; Visualization Design Considerations; How Will the User Respond to the Visualization?; How Will the Visualization Be Used?; How Should the Data Be Encoded?; Building Visualizations; Business Insights; Decisions and Actions; Prediction Layer; What Is Data Mining?; IKDDM Process Model for Data Mining

Business Understanding PhaseData Understanding; Data Preparation; Modeling (Data Mining); Evaluation; Deployment; Lessons Learned from Applying the Process Models to the Development of the PoCs; Conclusion; CHAPTER 6 DATA GOVERNANCE AND DATA QUALITY MANAGEMENT; Introduction; Data Governance and Data Quality; Data Quality Management Process; Stage 1: Defining Data Standards Quality Metrics; Stage 2: Data Quality Assessment; Stage 3: Data Maintenance/Stewardship; Stage 4: Data Life-Cycle Process Review; Conclusion; CHAPTER 7 DATA INTEGRATION: MANAGING DATA SOURCES FOR AGILITY; Introduction

Opportunities through Data Integration

Business intelligence (BI) has evolved over several years as organizations have extended their online transaction processing (OLTP) capabilities and applications to support their routine operations. With online analytical processing (OLAP), organizations have also established the capability to extract internal and external data from a variety of sources to specifically obtain intelligence about non-routine and often less-structured arrangements. BI therefore refers to applications and technologies that are used to gather, provide access to, and analyze data and information about the operations of an organization. It has the capability of providing comprehensive insight into the more volatile factors affecting the business and its operations, thereby facilitating enhanced decision-making quality and contributing to the creation of business value. Larger and more sophisticated organizations have long been exploiting these capabilities. Business Intelligence for Small and Medium-Sized Enterprises (SMEs) guides SMEs in replicating this experience to provide an agile roadmap toward business sustainability. The book points out that successful BI implementations have generated significant increases in revenue and cost savings, however, the failure rates are also very high. More importantly, it emphasizes that a full range of BI capabilities is not the exclusive purview of large organizations. It shows how SMEs make extensive use of BI techniques to develop the kind of agility endowing them with the organizational capability to sense and respond to opportunities and threats in an increasingly dynamic business environment. It points to the way to a market environment in which smaller organizations could have a larger role. In particular, the book explains that by establishing the agility to leverage internal and external data and information assets, SMEs can enhance their competitiveness by having a comprehensive understanding of the key to an agile roadmap for business sustainability.

OCLC-licensed vendor bibliographic record.