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Book Description

Big Data: A Business and Legal Guide supplies a clear understanding of the interrelationships between Big Data, the new business insights it reveals, and the laws, regulations, and contracting practices that impact the use of the insights and the data. Providing business executives and lawyers (in-house and in private practice) with an accessible primer on Big Data and its business implications, this book will enable readers to quickly grasp the key issues and effectively implement the right solutions to collecting, licensing, handling, and using Big Data.

The book brings together subject matter experts who examine a different area of law in each chapter and explain how these laws can affect the way your business or organization can use Big Data. These experts also supply recommendations as to the steps your organization can take to maximize Big Data opportunities without increasing risk and liability to your organization.

  • Provides a new way of thinking about Big Data that will help readers address emerging issues
  • Supplies real-world advice and practical ways to handle the issues
  • Uses examples pulled from the news and cases to illustrate points
  • Includes a non-technical Big Data primer that discusses the characteristics of Big Data and distinguishes it from traditional database models

Taking a cross-disciplinary approach, the book will help executives, managers, and counsel better understand the interrelationships between Big Data, decisions based on Big Data, and the laws, regulations, and contracting practices that impact its use. After reading this book, you will be able to think more broadly about the best way to harness Big Data in your business and establish procedures to ensure that legal considerations are part of the decision.

Table of Contents

  1. Dedications
  2. Disclaimer
  3. Why We Wrote This Book
  4. Acknowledgments
  5. About the Authors
  6. Contributors
  7. Chapter 1 - A Big Data Primer for Executives
    1. 1.1 What Is Big Data?
      1. 1.1.1 Characteristics of Big Data
      2. 1.1.2 Volume
      3. 1.1.3 The Internet of Things and Volume
      4. 1.1.4 Variety
      5. 1.1.5 Velocity
      6. 1.1.6 Validation
    2. 1.2. Cross-Disciplinary Approach, New Skills, and Investment
    3. 1.3 Acquiring Relevant Data
    4. 1.4 The Basics of How Big Data Technology Works
    5. 1.5 Summary
    6. Notes
  8. Chapter 2 - Overview of Information Security and Compliance: Seeing the Forest for the Trees
    1. 2.1 Introduction
    2. 2.2 What Kind of Data Should Be Protected?
    3. 2.3 Why Protections Are Important
    4. 2.4 Common Misconceptions about Information Security Compliance
    5. 2.5 Finding Common Threads in Compliance Laws and Regulations
    6. 2.6 Conclusion
    7. Note
  9. Chapter 3 - Information Security in Vendor and Business Partner Relationships
    1. 3.1 Introduction
    2. 3.2 Chapter Overview
    3. 3.3 The First Tool: A Due Diligence Questionnaire
    4. 3.4 The Second Tool: Key Contractual Protections
      1. 3.4.1 Warranties
      2. 3.4.2 Specific Information Security Obligations
      3. 3.4.3 Indemnity
      4. 3.4.4 Limitation of Liability
      5. 3.4.5 Confidentiality
      6. 3.4.6 Audit Rights
    5. 3.5 The Third Tool: An Information Security Requirements Exhibit
    6. 3.6 Conclusion
  10. Chapter 4 - Privacy and Big Data
    1. 4.1 Introduction
    2. 4.2 Privacy Laws, Regulations, and Principles That Have an Impact on Big Data
    3. 4.3 The Foundations of Privacy Compliance
    4. 4.4 Notice
    5. 4.5 Choice
    6. 4.6 Access
    7. 4.7 Fair Credit Reporting Act
    8. 4.8 Consumer Reports
    9. 4.9 Increased Scrutiny from the FTC
    10. 4.10 Implications for Businesses
    11. 4.11 Monetizing Personal Information: Are You a Data Broker?
    12. 4.12 The FTC’s Reclaim Your Name Initiative
    13. 4.13 Deidentification
    14. 4.14 Online Behavioral Advertising
    15. 4.15 Best Practices for Achieving Privacy Compliance for Big Data Initiatives
    16. 4.16 Data Flow Mapping Illustration
    17. Notes
  11. Chapter 5 - Federal and State Data Privacy Laws and Their Implications for the Creation and Use of Health Information Databases
    1. 5.1 Introduction
    2. 5.2 Chapter Overview
    3. 5.3 Key Considerations Related to Sources and Types of Data
    4. 5.4 PHI Collected from Covered Entities without Individual Authorization
      1. 5.4.1 Analysis for Covered Entities’ Health Care Operations
      2. 5.4.2 Creation and Use of Deidentified Data
      3. 5.4.3 Strategies for Aggregation and Deidentification of PHI by Business Associates
      4. 5.4.4 Marketing and Sale of PHI
      5. 5.4.5 Creation of Research Databases for Future Research Uses of PHI
      6. 5.4.6 Sensitive Information
    5. 5.5 Big Data Collected from Individuals
      1. 5.5.1 Personal Health Records
      2. 5.5.2 Mobile Technologies and Web-Based Applications
      3. 5.5.3 Conclusion
    6. 5.6 State Laws Limiting Further Disclosures of Health Information
      1. 5.6.1 State Law Restrictions Generally
      2. 5.6.2 Genetic Data: Informed Consent and Data Ownership
    7. 5.7 Conclusion
    8. Notes
  12. Chapter 6 - Big Data and Risk Assessment
    1. 6.1 Introduction
    2. 6.2 What Is the Strategic Purpose for the Use of Big Data?
    3. 6.3 How Does the Use of Big Data Have an Impact on the Market?
    4. 6.4 Does the Use of Big Data Result in Injury or Damage?
    5. 6.5 Does the Use of Big Data Analysis Have an Impact on Health Issues?
    6. 6.6 The Impact of Big Data on Discovery
    7. Notes
  13. Chapter 7 - Licensing Big Data
    1. 7.1 Overview
    2. 7.2 Protection of the Data/Database under Intellectual Property Law
      1. 7.2.1 Copyright
      2. 7.2.2 Trade Secrets
      3. 7.2.3 Contractual Protections for Big Data
    3. 7.3 Ownership Rights
    4. 7.4 License Grant
    5. 7.5 Anonymization
    6. 7.6 Confidentiality
    7. 7.7 Salting the Database
    8. 7.8 Termination
    9. 7.9 Fees/Royalties
      1. 7.9.1 Revenue Models
      2. 7.9.2 Price Protection
    10. 7.10 Audit
    11. 7.11 Warranty
    12. 7.12 Indemnification
    13. 7.13 Limitation of Liability
    14. 7.14 Conclusion
    15. Notes
  14. Chapter 8 - The Antitrust Laws and Big Data
    1. 8.1 Introduction
    2. 8.2 Overview of the Antitrust Laws
    3. 8.3 Big Data and Price-Fixing
    4. 8.4 Price-Fixing Risks
    5. 8.5 “Signaling” Risks
    6. 8.6 Steps to Reduce Price-Fixing and Signaling Risks
    7. 8.7 Information-Sharing Risks
    8. 8.8 Data Privacy and Security Policies as Facets of Nonprice Competition
    9. 8.9 Price Discrimination and the Robinson–Patman Act
    10. 8.10 Conclusion
    11. Notes
  15. Chapter 9 - The Impact of Big Data on Insureds, Insurance Coverage, and Insurers
    1. 9.1 Introduction
    2. 9.2 The Risks of Big Data
    3. 9.3 Traditional Insurance Likely Contains Significant Coverage Gaps for the Risks Posed by Big Data
    4. 9.4 Cyber Liability Insurance Coverage for the Risks Posed by Big Data
    5. 9.5 Considerations in the Purchase of Cyber Insurance Protection
    6. 9.6 Issues Related to Cyber Liability Insurance Coverage
    7. 9.7 The Use of Big Data by Insurers
    8. 9.8 Underwriting, Discounts, and the Trade Practices Act
    9. 9.9 The Privacy Act
    10. 9.10 Access to Personal Information
    11. 9.11 Correction of Personal Information
    12. 9.12 Disclosure of the Basis for Adverse Underwriting Decisions
    13. 9.13 Third-Party Data and the Privacy Act
    14. 9.14 The Privacy Regulation
    15. 9.15 Conclusion
    16. Notes
  16. Chapter 10 - Using Big Data to Manage Human Resources
    1. 10.1 Introduction
    2. 10.2 Using Big Data to Manage People
      1. 10.2.1 Absenteeism and Scheduling
      2. 10.2.2 Identifying Attributes of Success for Various Roles
      3. 10.2.3 Leading Change
      4. 10.2.4 Managing Employee Fraud
    3. 10.3 Regulating the Use of Big Data in Human Resource Management
    4. 10.4 Antidiscrimination under Title VII
    5. 10.5 The Genetic Information and Nondiscrimination Act of 2007
    6. 10.6 National Labor Relations Act
    7. 10.7 Fair Credit Reporting Act
    8. 10.8 State and Local Laws
    9. 10.9 Conclusion
    10. Notes
  17. Chapter 11 - Big Data Discovery
    1. 11.1 Introduction
    2. 11.2 Big Data, Big Preservation Problems
    3. 11.3 Big Data Preservation
      1. 11.3.1 The Duty to Preserve: A Time-Tested Legal Doctrine Meets Big Data
      2. 11.3.2 Avoiding Preservation Pitfalls
        1. 11.3.2.1 Failure to Flip the Off Switch
        2. 11.3.2.2 The Spreadsheet Error
        3. 11.3.2.3 The Never-Ending Hold
        4. 11.3.2.4 The Fire and Forget
        5. 11.3.2.5 Deputizing Custodians as Information Technology Personnel
      3. 11.3.3 Pulling the Litigation Hold Trigger
      4. 11.3.4 Big Data Preservation Triggers
    4. 11.4 Big Database Discovery
      1. 11.4.1 The Database Difference
      2. 11.4.2 Databases in Litigation
      3. 11.4.3 Cooperate Where You Can
      4. 11.4.4 Object to Unreasonable Demands
      5. 11.4.5 Be Specific
      6. 11.4.6 Talk about Database Discovery Early in the Process
    5. 11.5 Big Data Digging
      1. 11.5.1 Driving the CAR Process
      2. 11.5.2 The Clawback
    6. 11.6 Judicial Acceptance of CAR Methods
    7. 11.7 Conclusion
    8. Notes
  18. Glossary