Big Data Computing

Big Data Computing

by Rajendra Akerkar
Released December 2013
Publisher(s): Chapman and Hall/CRC
ISBN: 9781466578388

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Book description

Novel approaches and tools have emerged to tackle the challenges of Big Data. Moreover, the technology required for Big Data computing is developing at a satisfactory rate due to market forces and technological evolution. This book presents a mix of theory and industry cases that discuss the technical and practical issues related to Big Data in intelligent information management. It emphasizes the adoption and diffusion of Big Data tools and technologies in real practical applications.

Table of contents

  1. Front Cover
  2. Dedication
  3. Contents
  4. Preface (1/2)
  5. Preface (2/2)
  6. Acknowledgments
  7. Editor
  8. Contributors
  9. Section I: Introduction
    1. 1. Toward Evolving Knowledge Ecosystems for Big Data Understanding (1/11)
    2. 1. Toward Evolving Knowledge Ecosystems for Big Data Understanding (2/11)
    3. 1. Toward Evolving Knowledge Ecosystems for Big Data Understanding (3/11)
    4. 1. Toward Evolving Knowledge Ecosystems for Big Data Understanding (4/11)
    5. 1. Toward Evolving Knowledge Ecosystems for Big Data Understanding (5/11)
    6. 1. Toward Evolving Knowledge Ecosystems for Big Data Understanding (6/11)
    7. 1. Toward Evolving Knowledge Ecosystems for Big Data Understanding (7/11)
    8. 1. Toward Evolving Knowledge Ecosystems for Big Data Understanding (8/11)
    9. 1. Toward Evolving Knowledge Ecosystems for Big Data Understanding (9/11)
    10. 1. Toward Evolving Knowledge Ecosystems for Big Data Understanding (10/11)
    11. 1. Toward Evolving Knowledge Ecosystems for Big Data Understanding (11/11)
    12. 2. Tassonomy and Review of Big Data Solutions Navigation (1/10)
    13. 2. Tassonomy and Review of Big Data Solutions Navigation (2/10)
    14. 2. Tassonomy and Review of Big Data Solutions Navigation (3/10)
    15. 2. Tassonomy and Review of Big Data Solutions Navigation (4/10)
    16. 2. Tassonomy and Review of Big Data Solutions Navigation (5/10)
    17. 2. Tassonomy and Review of Big Data Solutions Navigation (6/10)
    18. 2. Tassonomy and Review of Big Data Solutions Navigation (7/10)
    19. 2. Tassonomy and Review of Big Data Solutions Navigation (8/10)
    20. 2. Tassonomy and Review of Big Data Solutions Navigation (9/10)
    21. 2. Tassonomy and Review of Big Data Solutions Navigation (10/10)
    22. 3. Big Data: Challenges and Opportunities (1/6)
    23. 3. Big Data: Challenges and Opportunities (2/6)
    24. 3. Big Data: Challenges and Opportunities (3/6)
    25. 3. Big Data: Challenges and Opportunities (4/6)
    26. 3. Big Data: Challenges and Opportunities (5/6)
    27. 3. Big Data: Challenges and Opportunities (6/6)
  10. Section II: Semantic Technologies and Big Data
    1. 4. Management of Big Semantic Data (1/8)
    2. 4. Management of Big Semantic Data (2/8)
    3. 4. Management of Big Semantic Data (3/8)
    4. 4. Management of Big Semantic Data (4/8)
    5. 4. Management of Big Semantic Data (5/8)
    6. 4. Management of Big Semantic Data (6/8)
    7. 4. Management of Big Semantic Data (7/8)
    8. 4. Management of Big Semantic Data (8/8)
    9. 5. Linked Data in Enterprise Integration (1/8)
    10. 5. Linked Data in Enterprise Integration (2/8)
    11. 5. Linked Data in Enterprise Integration (3/8)
    12. 5. Linked Data in Enterprise Integration (4/8)
    13. 5. Linked Data in Enterprise Integration (5/8)
    14. 5. Linked Data in Enterprise Integration (6/8)
    15. 5. Linked Data in Enterprise Integration (7/8)
    16. 5. Linked Data in Enterprise Integration (8/8)
    17. 6. Scalable End-User Access to Big Data (1/8)
    18. 6. Scalable End-User Access to Big Data (2/8)
    19. 6. Scalable End-User Access to Big Data (3/8)
    20. 6. Scalable End-User Access to Big Data (4/8)
    21. 6. Scalable End-User Access to Big Data (5/8)
    22. 6. Scalable End-User Access to Big Data (6/8)
    23. 6. Scalable End-User Access to Big Data (7/8)
    24. 6. Scalable End-User Access to Big Data (8/8)
    25. 7. Semantic Data Interoperability: The Key Problem of Big Data (1/6)
    26. 7. Semantic Data Interoperability: The Key Problem of Big Data (2/6)
    27. 7. Semantic Data Interoperability: The Key Problem of Big Data (3/6)
    28. 7. Semantic Data Interoperability: The Key Problem of Big Data (4/6)
    29. 7. Semantic Data Interoperability: The Key Problem of Big Data (5/6)
    30. 7. Semantic Data Interoperability: The Key Problem of Big Data (6/6)
  11. Section III: Big Data Processing
    1. 8. Big Data Exploration (1/5)
    2. 8. Big Data Exploration (2/5)
    3. 8. Big Data Exploration (3/5)
    4. 8. Big Data Exploration (4/5)
    5. 8. Big Data Exploration (5/5)
    6. 9. Big Data Processing with MapReduce (1/4)
    7. 9. Big Data Processing with MapReduce (2/4)
    8. 9. Big Data Processing with MapReduce (3/4)
    9. 9. Big Data Processing with MapReduce (4/4)
    10. 10. Efficient Processing of Stream Data over Persistent Data (1/6)
    11. 10. Efficient Processing of Stream Data over Persistent Data (2/6)
    12. 10. Efficient Processing of Stream Data over Persistent Data (3/6)
    13. 10. Efficient Processing of Stream Data over Persistent Data (4/6)
    14. 10. Efficient Processing of Stream Data over Persistent Data (5/6)
    15. 10. Efficient Processing of Stream Data over Persistent Data (6/6)
  12. Section IV: Big Data and Business
    1. 11. Economics of Big Data: A Value Perspective on State of the Art and Future Trends (1/6)
    2. 11. Economics of Big Data: A Value Perspective on State of the Art and Future Trends (2/6)
    3. 11. Economics of Big Data: A Value Perspective on State of the Art and Future Trends (3/6)
    4. 11. Economics of Big Data: A Value Perspective on State of the Art and Future Trends (4/6)
    5. 11. Economics of Big Data: A Value Perspective on State of the Art and Future Trends (5/6)
    6. 11. Economics of Big Data: A Value Perspective on State of the Art and Future Trends (6/6)
    7. 12. Advanced Data Analytics for Business (1/6)
    8. 12. Advanced Data Analytics for Business (2/6)
    9. 12. Advanced Data Analytics for Business (3/6)
    10. 12. Advanced Data Analytics for Business (4/6)
    11. 12. Advanced Data Analytics for Business (5/6)
    12. 12. Advanced Data Analytics for Business (6/6)
  13. Section V: Big Data Applications
    1. 13. Big Social Data Analysis (1/3)
    2. 13. Big Social Data Analysis (2/3)
    3. 13. Big Social Data Analysis (3/3)
    4. 14. Real-Time Big Data Processing for Domain Experts: An Application to Smart Buildings (1/7)
    5. 14. Real-Time Big Data Processing for Domain Experts: An Application to Smart Buildings (2/7)
    6. 14. Real-Time Big Data Processing for Domain Experts: An Application to Smart Buildings (3/7)
    7. 14. Real-Time Big Data Processing for Domain Experts: An Application to Smart Buildings (4/7)
    8. 14. Real-Time Big Data Processing for Domain Experts: An Application to Smart Buildings (5/7)
    9. 14. Real-Time Big Data Processing for Domain Experts: An Application to Smart Buildings (6/7)
    10. 14. Real-Time Big Data Processing for Domain Experts: An Application to Smart Buildings (7/7)
    11. 15. Big Data Application: Analyzing Real-Time Electric Meter Data (1/7)
    12. 15. Big Data Application: Analyzing Real-Time Electric Meter Data (2/7)
    13. 15. Big Data Application: Analyzing Real-Time Electric Meter Data (3/7)
    14. 15. Big Data Application: Analyzing Real-Time Electric Meter Data (4/7)
    15. 15. Big Data Application: Analyzing Real-Time Electric Meter Data (5/7)
    16. 15. Big Data Application: Analyzing Real-Time Electric Meter Data (6/7)
    17. 15. Big Data Application: Analyzing Real-Time Electric Meter Data (7/7)
    18. 16. Scaling of Geographic Space from the Perspective of City and Field Blocks and Using Volunteered Geographic Information (1/4)
    19. 16. Scaling of Geographic Space from the Perspective of City and Field Blocks and Using Volunteered Geographic Information (2/4)
    20. 16. Scaling of Geographic Space from the Perspective of City and Field Blocks and Using Volunteered Geographic Information (3/4)
    21. 16. Scaling of Geographic Space from the Perspective of City and Field Blocks and Using Volunteered Geographic Information (4/4)
    22. 17. Big Textual Data Analytics and Knowledge Management (1/8)
    23. 17. Big Textual Data Analytics and Knowledge Management (2/8)
    24. 17. Big Textual Data Analytics and Knowledge Management (3/8)
    25. 17. Big Textual Data Analytics and Knowledge Management (4/8)
    26. 17. Big Textual Data Analytics and Knowledge Management (5/8)
    27. 17. Big Textual Data Analytics and Knowledge Management (6/8)
    28. 17. Big Textual Data Analytics and Knowledge Management (7/8)
    29. 17. Big Textual Data Analytics and Knowledge Management (8/8)

Product information

  • Title: Big Data Computing
  • Author(s): Rajendra Akerkar
  • Release date: December 2013
  • Publisher(s): Chapman and Hall/CRC
  • ISBN: 9781466578388