| Description |
1 online resource (325 p.) |
| Contents |
Cover -- Half Title -- Title Page -- Copyright Page -- Table of Contents -- Foreword -- Preface -- Readers -- Figures -- Acknowledgments -- Authors -- 1 Artificial intelligence and machine learning: Opportunities for digital business -- Artificial intelligence in the context of business -- Artificial intelligence (AI) and machine learning (ML) as enablers of business optimization (BO) -- Subjective elements in BO -- Agility in BO -- Collaboration in BO -- Granularity in BO -- The technical-business continuum -- Strategic approach to business optimization -- BO as a redesign of business |
|
Developing a BO strategy -- Capabilities in BO -- AI, Big Data, and statistics -- Data, science, and analytics -- What and why of ML? -- Machine learning for Big Data -- Automation with ML -- Applying ML in practice for BO -- Business intelligence -- ML types in BO -- Supervised learning -- Unsupervised learning -- Reinforced learning -- Deep learning -- Feature engineering -- Digital business automation and optimization -- Value extraction from data -- Intelligent optimization -- Increasingly complex business situations -- Comparing automation and optimization -- Intelligent humanization |
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Challenges in AI-based business optimization -- Application challenges -- Business challenges -- Organizational culture challenges -- Knowledge management challenges -- Visualization and reporting -- User experience challenges -- Cybersecurity challenges -- Collaboration challenges -- COVID-19 pandemic and digital business -- Consolidation workshop -- Notes -- 2 Data to decisions: Evolving interrelationships -- Think data -- Think data: Handset, dataset, toolset, mindset -- Various aspects of think data -- Data characteristics -- Data as enabler of optimization -- Data to decisions pyramid |
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Layer 1: Data is a record of observations -- Layer 2: Information makes data understandable -- Layer 3: Analytics and services (collaborations) -- Layer 4: Knowledge and insights -- Layer 5: Decisions -- Big Data types and their characteristics for analytics -- The 3+1+1 (5) Vs of Big Data -- Sourcing of data -- Alternative data -- Data security and storage -- Data analytics in business process optimization -- Data analytics -- Business process optimization -- Establishing the data context -- Tools and techniques for BO -- Data analytics design for BO -- Granularity of analytics in BO |
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User experience analysis and BO -- Self-serve analytics in BO -- Data clusters and segmentation -- Horizontal and vertical clustering -- Segmentation -- Clusters and segments in practice -- Data-driven decisions -- Nature and types of decisions -- Automation -- Prediction -- Experience -- Intuition -- Data analytics for business agility -- Consolidation workshop -- Notes -- 3 Digital leadership: Strategies for AI adoption -- Strategizing for business optimization -- Envisioning digital business strategy for AI -- Digital strategies are holistic -- Customer value is the goal |
| Notes |
Description based upon print version of record |
| Subject |
Artificial intelligence -- Economic aspects
|
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Information technology -- Management
|
|
Machine learning
|
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Artificial intelligence -- Economic aspects.
|
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Information technology -- Management.
|
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Machine learning.
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| Form |
Electronic book
|
| Author |
Gonsalves, Tad
|
| ISBN |
9781000409475 |
|
1000409473 |
|
