Cover
Praise For This Book
Title Page
Copyright
About the Authors
Acknowledgments
Contents at a Glance
Contents
Foreword for Smarter Data Science
Epigraph
Preamble
Chapter 1 Climbing the AI Ladder
Readying Data for AI
Technology Focus Areas
Taking the Ladder Rung by Rung
Constantly Adapt to Retain Organizational Relevance
Data-Based Reasoning Is Part and Parcel in the Modern Business
Toward the AI-Centric Organization
Summary
Chapter 2 Framing Part I: Considerations for Organizations Using AI
Data-Driven Decision-Making; Using Interrogatives to Gain Insight
The Trust Matrix
The Importance of Metrics and Human Insight
Democratizing Data and Data Science
Aye, a Prerequisite: Organizing Data Must Be a Forethought
Preventing Design Pitfalls
Facilitating the Winds of Change: How Organized Data Facilitates Reaction Time
Quae Quaestio (Question Everything)
Summary
Chapter 3 Framing Part II: Considerations for Working with Data and AI
Personalizing the Data Experience for Every User
Context Counts: Choosing the Right Way to Display Data; Ethnography: Improving Understanding Through Specialized Data
Data Governance and Data Quality
The Value of Decomposing Data
Providing Structure Through Data Governance
Curating Data for Training
Additional Considerations for Creating Value
Ontologies: A Means for Encapsulating Knowledge
Fairness, Trust, and Transparency in AI Outcomes
Accessible, Accurate, Curated, and Organized
Summary
Chapter 4 A Look Back on Analytics: More Than One Hammer
Been Here Before: Reviewing the Enterprise Data Warehouse
Drawbacks of the Traditional Data Warehouse
Paradigm Shift; Modern Analytical Environments: The Data Lake
By Contrast
Indigenous Data
Attributes of Difference
Elements of the Data Lake
The New Normal: Big Data Is Now Normal Data
Liberation from the Rigidity of a Single Data Model
Streaming Data
Suitable Tools for the Task
Easier Accessibility
Reducing Costs
Scalability
Data Management and Data Governance for AI
Schema-on-Read vs. Schema-on-Write
Summary
Chapter 5 A Look Forward on Analytics: Not Everything Can Be a Nail
A Need for Organization
The Staging Zone
The Raw Zone; The Discovery and Exploration Zone
The Aligned Zone
The Harmonized Zone
The Curated Zone
Data Topologies
Zone Map
Data Pipelines
Data Topography
Expanding, Adding, Moving, and Removing Zones
Enabling the Zones
Ingestion
Data Governance
Data Storage and Retention
Data Processing
Data Access
Management and Monitoring
Metadata
Summary
Chapter 6 Addressing Operational Disciplines on the AI Ladder
A Passage of Time
Create
Stability
Barriers
Complexity
Execute
Ingestion
Visibility
Compliance
Operate
Quality.