| Description |
xvi, 150 pages ; 25 cm |
| Contents |
Machine generated contents note: Digital Business Trends -- Conceptions of Agility -- Business Intelligence as an Enabler of Agility -- SMEs, Business Intelligence and Agility -- About this Book -- pt. I BL LANDSCAPE -- OPPORTUNITIES FOR SMEs -- ch. 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 SMEs -- Distribution and Retail -- Credit and Micro-Finance Services -- ch. 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 -- |
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Contents note continued: Step 3 BI Portfolio Evaluation -- Step 4 Proof of Concept Prototypes -- Strategic Business Intelligence Roadmap -- Findings from Applying AIMS-BI -- Conclusion -- pt. II Navigating the Agile BI Process -- ch. 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 -- ch. 4 Creating BI Portfolios -- Introduction -- The Discovery of BI Opportunities -- BI Portfolio Evaluation -- Example: BI Opportunity Discovery and Portfolio Evaluation -- Conclusion -- ch. 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) -- |
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Contents note continued: 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 Phase -- Data Understanding -- Data Preparation -- Modeling (Data Mining) -- Evaluation -- Deployment -- Lessons Learned from Applying the Process Models to the Development of the PoCs -- Conclusion -- ch. 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 -- |
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Contents note continued: ch. 7 Data Integration: Managing Data Sources for Agility -- Introduction -- Opportunities through Data Integration -- Key Deliverables from Realizing Integration Opportunities -- Common Approach to Data Integration -- Possible Integration Approaches -- Examples of Data Integration Techniques -- Physical Integration -- Virtual Integration -- Physical vs. Virtual Integration -- Selecting a Data Integration Approach -- Recommendations for SMEs -- Conclusion -- pt. III A Blueprint for Action -- ch. 8 Developing a Roadmap for Strategic Business Intelligence -- Introduction -- Information Management (IM) Maturity Assessment (Capability Gaps) -- Proof of Concept (PoC) Prototypes -- Data Quality -- Data Integration -- Architecture of a Business Intelligence (BI) Roadmap -- Performance -- People -- Process -- Platform -- Example Roadmap -- Portfolio of BI Initiatives -- Navigating the BI Roadmap -- Conclusion -- ch. 9 Creating Business Value from Data Assets -- |
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Contents note continued: Introduction -- Measuring Value of your Data Assets -- Method of Information Value Assessment -- Managing the Value of your Data Assets -- Benefits Realization Management (BRM) -- Conclusion/Recommendations |
| Summary |
"Small and medium-sized enterprises (SMEs) have an excellent opportunity to harness their natural agility to compete and to do this they should look to business analytics. This book presents a process model that can be adapted by organizations looking to acquire agility through analytics. It describes the steps of the model and real-world examples"-- |
| Subject |
Business intelligence
|
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Small business -- Management
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Strategic planning
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| Author |
McNaughton, Maurice L., author
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Mansingh, Gunjan, author
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| LC no. |
2019020866 |
| ISBN |
9781138584211 |
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