The Resource Big Data revolution : what farmers, doctors and insurance agents teach us about discovering Big Data patterns, Rob Thomas, Patrick McSharry

Big Data revolution : what farmers, doctors and insurance agents teach us about discovering Big Data patterns, Rob Thomas, Patrick McSharry

Label
Big Data revolution : what farmers, doctors and insurance agents teach us about discovering Big Data patterns
Title
Big Data revolution
Title remainder
what farmers, doctors and insurance agents teach us about discovering Big Data patterns
Statement of responsibility
Rob Thomas, Patrick McSharry
Creator
Contributor
Author
Subject
Language
eng
Cataloging source
NhCcYBP
http://library.link/vocab/creatorName
Thomas, Rob
Dewey number
658/.0557
Index
no index present
LC call number
HF5548.2
LC item number
.T384 2015
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorName
  • McSharry, Patrick
  • ProQuest (Firm)
http://library.link/vocab/subjectName
  • Decision making
  • Big data
  • Data mining
  • Organizational effectiveness
Label
Big Data revolution : what farmers, doctors and insurance agents teach us about discovering Big Data patterns, Rob Thomas, Patrick McSharry
Link
https://ebookcentral.proquest.com/lib/umanitoba/detail.action?docID=1895779
Instantiates
Publication
Antecedent source
unknown
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Outline
  • ch. 7
  • Government and Society
  • Egypt, 2011
  • Social Media
  • Intelligence
  • Snowden Effect
  • Privacy Risk Versus Reward
  • Observation or Surveillance
  • Development Targets
  • Open Data
  • Part I "The Revolution Starts Now: 9 Industries Transforming with Data"
  • Hackathons
  • Open Access
  • Ensuring Personal Protection
  • Private Clouds
  • Sanitizing Data
  • Evidence-Based Policy
  • Public-Private Partnerships
  • Impact Bonds
  • Social Impact Bond
  • Development Impact Bonds
  • Part II "Learning from Patterns in Big Data"
  • Role of Big Data
  • Egypt, 2011 (Continued)
  • ch. 8
  • Corporate Sustainability
  • City of London
  • Global Megaforces
  • Population
  • Carbon Footprint
  • Water Scarcity
  • Environmental Risk
  • Part III "Leading the Revolution"
  • BP and Exxon Mobile
  • Early Warning Systems
  • Social Media
  • Risk and Resilience
  • Measuring Sustainability
  • Long-Term Decision Making
  • Stranded Assets
  • City of London (Continued)
  • ch. 9
  • Weather and Energy
  • Storytelling (Continued)
  • India, 2012
  • Weather
  • Forecasting the Weather
  • When are Weather Forecasts Wrong?
  • Chaos
  • Ensemble Forecasts
  • Communication
  • Renewable Energy
  • Solar, Hydro, and Wind Power
  • Volatile or Intermittent Supply
  • ch. 1
  • Energy Consumption
  • Smart Meters
  • Intelligent Demand-Side Management
  • India, 2012 (Continued)
  • ch. 10
  • Pattern Recognition
  • Elements of Success Rhyme
  • Pattern Recognition: A Gift or Trap?
  • What Fish Teach Us About Pattern Recognition
  • Bayes' Theorem
  • Transforming Farms with Data
  • Tsukiji Market
  • Pattern Recognition
  • Rochester Institute of Technology
  • Method for Recognizing Patterns
  • Elements of Success Rhyme (Continued)
  • ch. 11
  • Why Patterns in Big Data Have Emerged
  • Meatpacking District
  • Business Models in the Data Era
  • Data as a Competitive Advantage
  • California, 2013
  • Data Improves Existing Products or Services
  • Data as the Product
  • Dun & Bradstreet
  • CoStar
  • IHS
  • Meatpacking District (Continued)
  • ch. 12
  • Patterns in Big Data
  • Data Factor
  • Summary of Big Data Patterns
  • Brief History of Farming
  • Redefining a Skilled Worker
  • Creating and Utilizing New Sources of Data
  • Building New Data Applications
  • Transforming and Creating New Business Processes
  • Data Collection for Competitive Advantage
  • Exposing Opinion-Based Biases
  • Real-Time Monitoring and Decision Making
  • Social Networks Leveraging and Creating Data
  • Deconstructing the Value Chain
  • New Product Offerings
  • Data Era
  • Building for Customers Instead of Markets
  • Tradeoff Between Privacy and Insight
  • Changing the Definition of a Product
  • Inverting the Search Paradigm for Data Discovery
  • Data Security
  • New Partnerships Founded on Data
  • Shortening the Innovation Lifecycle
  • Defining New Channels to Market
  • New Economic Models
  • Forecasting and Predicting Future Events
  • Machine generated contents note:
  • Potato Farming
  • Changing Incentives
  • New Partnerships (Public/Private)
  • Real-Time Monitoring and Decision Making (Early Warning Systems)
  • Framework for Big Data Patterns
  • ch. 13
  • Data Opportunity
  • What Oil Teaches Us About Data
  • Bain Study
  • Seizing the Opportunity
  • ch. 14
  • Precision Farming
  • Porsche
  • Rome
  • Ferdinand Porsche
  • Birth of Porsche
  • Porsche Sports Car
  • Porsche Today
  • Rome (Continued)
  • ch. 15
  • Puma
  • Herzogenaurach
  • Capturing Farm Data
  • Advertising Wars
  • Jochen Zeitz
  • Environmental Profit and Loss
  • Herzogenaurach (Continued)
  • ch. 16
  • Methodology for Applying Big Data Patterns
  • Introduction
  • Method
  • Step 1: Understand Data Assets
  • Patterns
  • Deere & Company Versus Monsanto
  • Step 2: Explore Data
  • Challenges
  • Questions
  • Hypotheses
  • Data
  • Models
  • Statistical Significance
  • Step 3: Design the Future
  • Patterns
  • Step 4: Design a Data-Driven Business Model
  • Integrated Farming Systems
  • Patterns
  • Step 5: Transform Business Processes for the Data Era
  • Patterns
  • Step 6: Design for Governance and Security
  • Patterns
  • Step 7: Share Metrics and Incentives
  • ch. 17
  • Big Data Architecture
  • Introduction
  • Architect for the Future
  • Data Prevails
  • Lessons from Stuttgart
  • Big Data Reference Architectures
  • Leveraging Investments in Architecture
  • Big Data Reference Architectures
  • Business View
  • Logical View
  • ch. 18
  • Business View Reference Architecture
  • Introduction
  • Men's Trunk: A Retailer in the Data Era
  • Climate Corporation
  • Business View Reference Architecture
  • Answer Fabric
  • Data Virtualization
  • Data Engines
  • Management
  • Data Governance
  • User Interface, Applications, and Business Processes
  • Summary
  • ch. 19
  • Logical View Reference Architecture
  • Growsafe Systems
  • Introduction
  • Men's Trunk: A Retailer in the Data Era (Continued)
  • Logical View Reference Architecture
  • Data Ingest
  • Analytics
  • Discovery
  • Landing
  • Operational Warehouse
  • Information Insight
  • Operational Data
  • Farm of the Future
  • Governance
  • Men's Trunk: A Retailer in the Data Era (Continued)
  • ch. 20
  • Architecture of the Future
  • Men's Trunk: A Retailer in the Data Era (Continued)
  • Men's Trunk: Applying the Methodology
  • Step 1: Understand Data Assets
  • Step 2: Explore the Data
  • Step 3: Design the Future
  • Step 4: Design a Data-Driven Business Model
  • California, 2013 (Continued)
  • Step 5: Transform Business Processes for the Data Era
  • Step 6: Design for Governance and Security
  • Step 7: Share Metrics and Incentives
  • Men's Trunk: The Business View Reference Architecture
  • Answer Fabric
  • Data Virtualization
  • Data Engines
  • Management
  • Data Governance
  • User Interface, Applications, and Business Processes
  • Berkeley, 1930s
  • ch. 2
  • Men's Trunk: The Logical View Reference Architecture
  • Approach
  • Men's Trunk: A Retailer in the Data Era (Continued)
  • Time is Now
  • Taking Action
  • Fear not Usual Competitors
  • Future
  • Why Doctors Will Have Math Degrees
  • United States, 2014
  • History of Medical Education
  • Scientific Method
  • Rise of Specialists
  • We Have a Problem
  • Ben Goldacre
  • Vinod Khosla
  • Data Era
  • Pattern Recognition
  • Collecting Data
  • Telemedicine
  • Innovating with Data
  • Implications of a Data-Driven Medical World
  • Future of Medical School
  • Typical Medical School
  • Medical School for the Data Era
  • United States, 2030
  • ch. 3
  • Revolutionizing Insurance: Why Actuaries Will Become Data Scientists
  • Nelson Peltz
  • Middle of Somewhere, 2012
  • Short History of Property & Casualty Insurance and Underwriting
  • Actuarial Science In Insurance
  • Pensions, Insurance, Leases
  • Compound Interest
  • Probability
  • Mortality Data
  • Modern-Day Insurance
  • Eight Weeks to Eight Days
  • Online Policies
  • Committing to One Percent
  • Data Era
  • Dynamic Risk Management
  • Catastrophe Risk
  • Open Access Modeling
  • Opportunities
  • Middle of Somewhere, 2012 (Continued)
  • ch. 4
  • Personalizing Retail and Fashion
  • Karolina
  • Brief History of Retail
  • Big Data Revolution
  • Retail Eras
  • Aristide Boucicaut
  • Shift
  • Data Era
  • Stitch Fix
  • Keaton Row
  • Zara
  • Karolina (Continued)
  • ch. 5
  • Transforming Customer Relationships with Data
  • Storytelling
  • Buying a House
  • Brief History of Customer Service
  • Customer Service Over Time
  • Boeing
  • Financial Services
  • Data Era
  • Automobile Manufacturer
  • Zendesk
  • Buying a House (Continued)
  • ch. 6
  • Objective
  • Intelligent Machines
  • Denmark
  • Intelligent Machines
  • Machine Data
  • Data Era
  • General Electric
  • Drones
  • Tesla
  • Networks of Data
  • Denmark (Continued)
Dimensions
unknown
Extent
1 online resource.
File format
unknown
Form of item
online
Isbn
9781118943731
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Quality assurance targets
not applicable
Reformatting quality
unknown
Reproduction note
Electronic reproduction.
Sound
unknown sound
Specific material designation
remote
System control number
(NhCcYBP)EBC1895779
Label
Big Data revolution : what farmers, doctors and insurance agents teach us about discovering Big Data patterns, Rob Thomas, Patrick McSharry
Link
https://ebookcentral.proquest.com/lib/umanitoba/detail.action?docID=1895779
Publication
Antecedent source
unknown
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Outline
  • ch. 7
  • Government and Society
  • Egypt, 2011
  • Social Media
  • Intelligence
  • Snowden Effect
  • Privacy Risk Versus Reward
  • Observation or Surveillance
  • Development Targets
  • Open Data
  • Part I "The Revolution Starts Now: 9 Industries Transforming with Data"
  • Hackathons
  • Open Access
  • Ensuring Personal Protection
  • Private Clouds
  • Sanitizing Data
  • Evidence-Based Policy
  • Public-Private Partnerships
  • Impact Bonds
  • Social Impact Bond
  • Development Impact Bonds
  • Part II "Learning from Patterns in Big Data"
  • Role of Big Data
  • Egypt, 2011 (Continued)
  • ch. 8
  • Corporate Sustainability
  • City of London
  • Global Megaforces
  • Population
  • Carbon Footprint
  • Water Scarcity
  • Environmental Risk
  • Part III "Leading the Revolution"
  • BP and Exxon Mobile
  • Early Warning Systems
  • Social Media
  • Risk and Resilience
  • Measuring Sustainability
  • Long-Term Decision Making
  • Stranded Assets
  • City of London (Continued)
  • ch. 9
  • Weather and Energy
  • Storytelling (Continued)
  • India, 2012
  • Weather
  • Forecasting the Weather
  • When are Weather Forecasts Wrong?
  • Chaos
  • Ensemble Forecasts
  • Communication
  • Renewable Energy
  • Solar, Hydro, and Wind Power
  • Volatile or Intermittent Supply
  • ch. 1
  • Energy Consumption
  • Smart Meters
  • Intelligent Demand-Side Management
  • India, 2012 (Continued)
  • ch. 10
  • Pattern Recognition
  • Elements of Success Rhyme
  • Pattern Recognition: A Gift or Trap?
  • What Fish Teach Us About Pattern Recognition
  • Bayes' Theorem
  • Transforming Farms with Data
  • Tsukiji Market
  • Pattern Recognition
  • Rochester Institute of Technology
  • Method for Recognizing Patterns
  • Elements of Success Rhyme (Continued)
  • ch. 11
  • Why Patterns in Big Data Have Emerged
  • Meatpacking District
  • Business Models in the Data Era
  • Data as a Competitive Advantage
  • California, 2013
  • Data Improves Existing Products or Services
  • Data as the Product
  • Dun & Bradstreet
  • CoStar
  • IHS
  • Meatpacking District (Continued)
  • ch. 12
  • Patterns in Big Data
  • Data Factor
  • Summary of Big Data Patterns
  • Brief History of Farming
  • Redefining a Skilled Worker
  • Creating and Utilizing New Sources of Data
  • Building New Data Applications
  • Transforming and Creating New Business Processes
  • Data Collection for Competitive Advantage
  • Exposing Opinion-Based Biases
  • Real-Time Monitoring and Decision Making
  • Social Networks Leveraging and Creating Data
  • Deconstructing the Value Chain
  • New Product Offerings
  • Data Era
  • Building for Customers Instead of Markets
  • Tradeoff Between Privacy and Insight
  • Changing the Definition of a Product
  • Inverting the Search Paradigm for Data Discovery
  • Data Security
  • New Partnerships Founded on Data
  • Shortening the Innovation Lifecycle
  • Defining New Channels to Market
  • New Economic Models
  • Forecasting and Predicting Future Events
  • Machine generated contents note:
  • Potato Farming
  • Changing Incentives
  • New Partnerships (Public/Private)
  • Real-Time Monitoring and Decision Making (Early Warning Systems)
  • Framework for Big Data Patterns
  • ch. 13
  • Data Opportunity
  • What Oil Teaches Us About Data
  • Bain Study
  • Seizing the Opportunity
  • ch. 14
  • Precision Farming
  • Porsche
  • Rome
  • Ferdinand Porsche
  • Birth of Porsche
  • Porsche Sports Car
  • Porsche Today
  • Rome (Continued)
  • ch. 15
  • Puma
  • Herzogenaurach
  • Capturing Farm Data
  • Advertising Wars
  • Jochen Zeitz
  • Environmental Profit and Loss
  • Herzogenaurach (Continued)
  • ch. 16
  • Methodology for Applying Big Data Patterns
  • Introduction
  • Method
  • Step 1: Understand Data Assets
  • Patterns
  • Deere & Company Versus Monsanto
  • Step 2: Explore Data
  • Challenges
  • Questions
  • Hypotheses
  • Data
  • Models
  • Statistical Significance
  • Step 3: Design the Future
  • Patterns
  • Step 4: Design a Data-Driven Business Model
  • Integrated Farming Systems
  • Patterns
  • Step 5: Transform Business Processes for the Data Era
  • Patterns
  • Step 6: Design for Governance and Security
  • Patterns
  • Step 7: Share Metrics and Incentives
  • ch. 17
  • Big Data Architecture
  • Introduction
  • Architect for the Future
  • Data Prevails
  • Lessons from Stuttgart
  • Big Data Reference Architectures
  • Leveraging Investments in Architecture
  • Big Data Reference Architectures
  • Business View
  • Logical View
  • ch. 18
  • Business View Reference Architecture
  • Introduction
  • Men's Trunk: A Retailer in the Data Era
  • Climate Corporation
  • Business View Reference Architecture
  • Answer Fabric
  • Data Virtualization
  • Data Engines
  • Management
  • Data Governance
  • User Interface, Applications, and Business Processes
  • Summary
  • ch. 19
  • Logical View Reference Architecture
  • Growsafe Systems
  • Introduction
  • Men's Trunk: A Retailer in the Data Era (Continued)
  • Logical View Reference Architecture
  • Data Ingest
  • Analytics
  • Discovery
  • Landing
  • Operational Warehouse
  • Information Insight
  • Operational Data
  • Farm of the Future
  • Governance
  • Men's Trunk: A Retailer in the Data Era (Continued)
  • ch. 20
  • Architecture of the Future
  • Men's Trunk: A Retailer in the Data Era (Continued)
  • Men's Trunk: Applying the Methodology
  • Step 1: Understand Data Assets
  • Step 2: Explore the Data
  • Step 3: Design the Future
  • Step 4: Design a Data-Driven Business Model
  • California, 2013 (Continued)
  • Step 5: Transform Business Processes for the Data Era
  • Step 6: Design for Governance and Security
  • Step 7: Share Metrics and Incentives
  • Men's Trunk: The Business View Reference Architecture
  • Answer Fabric
  • Data Virtualization
  • Data Engines
  • Management
  • Data Governance
  • User Interface, Applications, and Business Processes
  • Berkeley, 1930s
  • ch. 2
  • Men's Trunk: The Logical View Reference Architecture
  • Approach
  • Men's Trunk: A Retailer in the Data Era (Continued)
  • Time is Now
  • Taking Action
  • Fear not Usual Competitors
  • Future
  • Why Doctors Will Have Math Degrees
  • United States, 2014
  • History of Medical Education
  • Scientific Method
  • Rise of Specialists
  • We Have a Problem
  • Ben Goldacre
  • Vinod Khosla
  • Data Era
  • Pattern Recognition
  • Collecting Data
  • Telemedicine
  • Innovating with Data
  • Implications of a Data-Driven Medical World
  • Future of Medical School
  • Typical Medical School
  • Medical School for the Data Era
  • United States, 2030
  • ch. 3
  • Revolutionizing Insurance: Why Actuaries Will Become Data Scientists
  • Nelson Peltz
  • Middle of Somewhere, 2012
  • Short History of Property & Casualty Insurance and Underwriting
  • Actuarial Science In Insurance
  • Pensions, Insurance, Leases
  • Compound Interest
  • Probability
  • Mortality Data
  • Modern-Day Insurance
  • Eight Weeks to Eight Days
  • Online Policies
  • Committing to One Percent
  • Data Era
  • Dynamic Risk Management
  • Catastrophe Risk
  • Open Access Modeling
  • Opportunities
  • Middle of Somewhere, 2012 (Continued)
  • ch. 4
  • Personalizing Retail and Fashion
  • Karolina
  • Brief History of Retail
  • Big Data Revolution
  • Retail Eras
  • Aristide Boucicaut
  • Shift
  • Data Era
  • Stitch Fix
  • Keaton Row
  • Zara
  • Karolina (Continued)
  • ch. 5
  • Transforming Customer Relationships with Data
  • Storytelling
  • Buying a House
  • Brief History of Customer Service
  • Customer Service Over Time
  • Boeing
  • Financial Services
  • Data Era
  • Automobile Manufacturer
  • Zendesk
  • Buying a House (Continued)
  • ch. 6
  • Objective
  • Intelligent Machines
  • Denmark
  • Intelligent Machines
  • Machine Data
  • Data Era
  • General Electric
  • Drones
  • Tesla
  • Networks of Data
  • Denmark (Continued)
Dimensions
unknown
Extent
1 online resource.
File format
unknown
Form of item
online
Isbn
9781118943731
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Quality assurance targets
not applicable
Reformatting quality
unknown
Reproduction note
Electronic reproduction.
Sound
unknown sound
Specific material designation
remote
System control number
(NhCcYBP)EBC1895779

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