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Data_flood: Helping the Navy Address the Rising Tide of Sensor Information

Data_flood: Helping the Navy Address the Rising Tide of Sensor Information

Porche, Isaac R., author

Navy analysts are struggling to keep pace with the growing flood of data collected by intelligence, surveillance, and reconnaissance sensors. This challenge is sure to intensify as the Navy continues to field new and additional sensors. The authors explore options for solving the Navy's "big data" challenge, considering changes across four dimensions: people, tools and technology, data and data architectures, and demand and demand management

eBook, Electronic resource, Book. English. Electronic books.
Published Santa Monica, CA : RAND/National Defense Research Instittue 2014

This resource is available electronically from the following locations

Details

Statement of responsibility: Isaac R. Proche III [and 4 others]
ISBN: 0833084305, 0833084321, 9780833084293, 9780833084309, 9780833084323
Note: Print version record.
Note: Includes bibliographical references.
Physical Description: 1 online resource (xx, 63 pages)
Subject: TECHNOLOGY & ENGINEERING Military Science.; BUSINESS & ECONOMICS Economics General.; Electronic intelligence.; United States. Navy.; HISTORY Military Other.; United States.; Electronic intelligence United States.
Local note: JSTOR Books at JSTOR Open Access

Contents

  1. Cover
  2. Title Page
  3. Copyright
  4. Preface
  5. Contents
  6. Figures
  7. Tables
  8. Summary
  9. Acknowledgments
  10. Abbreviations
  11. Chapter One: Big Data: Challenges and Opportunities
  12. What Is "Big Data"?
  13. How Big Is Big?
  14. The Navy's Big Data Challenge
  15. The Navy's Big Data Opportunity
  16. Chapter Two: What the Navy Wants from Big Data
  17. Where Am I?
  18. Where Are My Friends?
  19. Where Is the Enemy?
  20. Where Is Everyone Else?
  21. Situational Awareness: A Vital Goal
  22. Chapter Three: Barriers to Benefiting from Big Data
  23. Timely Consumption
  24. Accurate Integration
  25. How Analysts Cope Today.
  26. Chapter Four: Dynamically Managing Analyst WorkloadsChapter Five: Alternatives for Dealing with Big Data
  27. Baseline
  28. Alternative 1: Applications (Adding More Tools to the Baseline)
  29. Alternative 2: Consolidation (Adopt a Service-Oriented Environment)
  30. Alternative 3: Cloud (Join the Distributed Cloud)
  31. Advantages and Disadvantages of the Alternatives
  32. Differences Among the Baseline and the Alternatives
  33. Summary of the Baseline and Alternatives
  34. Chapter Six: Analysis
  35. Performance
  36. Cost
  37. Risk
  38. Chapter Seven: Recommendations
  39. Move Forward with Alternative 3 (Cloud).
  40. Extend Aspects and Components of Alternative 3 to Other Programs and SituationsPrepare for Culture Change; Appendix: Additional Information; Bibliography.