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Smarter data science : succeeding with enterprise-grade data and AI projects / / Neal Fishman, Cole Stryker
| Smarter data science : succeeding with enterprise-grade data and AI projects / / Neal Fishman, Cole Stryker |
| Autore | Fishman Neal |
| Pubbl/distr/stampa | Indianapolis : , : John Wiley and Sons, , 2020 |
| Descrizione fisica | 1 online resource (307 pages) |
| Disciplina | 495.932 |
| Soggetto topico |
Management information systems
Database management Business - Management Information storage and retrieval systems - Reliability COMPUTERS - Data Science - Data Modeling & Design |
| ISBN |
1-119-69342-X
1-119-69438-8 1-119-69798-0 |
| Classificazione |
007.609
005.7 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 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. |
| Record Nr. | UNINA-9910555077903321 |
Fishman Neal
|
||
| Indianapolis : , : John Wiley and Sons, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Smarter data science : succeeding with enterprise-grade data and AI projects / / Neal Fishman, Cole Stryker
| Smarter data science : succeeding with enterprise-grade data and AI projects / / Neal Fishman, Cole Stryker |
| Autore | Fishman Neal |
| Pubbl/distr/stampa | Indianapolis : , : John Wiley and Sons, , 2020 |
| Descrizione fisica | 1 online resource (307 pages) |
| Disciplina | 495.932 |
| Soggetto topico |
Management information systems
Database management Business - Management Information storage and retrieval systems - Reliability COMPUTERS - Data Science - Data Modeling & Design |
| ISBN |
1-119-69342-X
1-119-69438-8 1-119-69798-0 |
| Classificazione |
007.609
005.7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 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. |
| Record Nr. | UNINA-9910812216103321 |
|
Fishman Neal
|
||
| Indianapolis : , : John Wiley and Sons, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||