Handbook of research on big data storage and visualization techniques:
"This book presents the concepts of big data, explores its analytics and technologies and their applications and develops an understanding of issues pertaining to the use of big data in multidisciplinary fields. It explores big data through the historical and technical background, architecture,...
Gespeichert in:
| Weitere Verfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA)
IGI Global
[c2018]
|
| Schlagworte: | |
| Online-Zugang: | DE-862 DE-863 |
| Zusammenfassung: | "This book presents the concepts of big data, explores its analytics and technologies and their applications and develops an understanding of issues pertaining to the use of big data in multidisciplinary fields. It explores big data through the historical and technical background, architecture, open-source and commercial programming systems, analytics, state of practice in industry, and other topics"-- |
| Beschreibung: | 46 PDFs (2 volumes) Also available in print. |
| Format: | Mode of access: World Wide Web. |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9781522531432 |
| Zugangseinschränkungen: | Restricted to subscribers or individual electronic text purchasers. |
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| 245 | 0 | 0 | |a Handbook of research on big data storage and visualization techniques |c Richard S. Segall and Jeffrey S. Cook, editors. |
| 246 | 3 | 0 | |a Big data storage and visualization techniques |
| 264 | 1 | |a Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) |b IGI Global |c [c2018] | |
| 300 | |a 46 PDFs (2 volumes) | ||
| 336 | |a text |2 rdacontent | ||
| 337 | |a electronic |2 isbdmedia | ||
| 338 | |a online resource |2 rdacarrier | ||
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Volume I. Section 1. Introduction to big data and storage systems. Chapter 1. Overview of big data and its visualization ; Chapter 2. Overview of big-data-intensive storage and its technologies -- Section 2. Big data technologies and architectural patterns. Chapter 3. Database systems for big data storage and retrieval ; Chapter 4. Hadoop framework for handling big data needs ; Chapter 5. Role of open source software in big data storage -- Section 3. Big data in clouds, clusters, and grids. Chapter 6. Big data tools for computing on clouds and grids ; Chapter 7. A review of security challenges in cloud storage of big data ; Chapter 8. Architecture for big data storage in different cloud deployment models -- Section 4. Big data processing for storage and visualization. Chapter 9. Programming and pre-processing systems for big data storage and visualization ; Chapter 10. High performance storage for big data analytics and visualization ; Chapter 11. Big data in massive parallel processing: a multi-core processors perspective ; Chapter 12. Distributed streaming big data analytics for internet of things (IoT) -- Section 5. Applications of big data storage. Chapter 13. Scalable data warehouse architecture: a higher education case study ; Chapter 14. Resource provisioning and scheduling of big data processing jobs ; Chapter 15. Issues and methods for access, storage, and analysis of data from online social communities ; Chapter 16. Big data storage for the modeling of historical time series solar irradiations -- Volume II. Section 6. Visualization tools and techniques. Chapter 17. Big data visualization tools and techniques ; Chapter 18. The image as big data toolkit: an application case study in image analysis, feature recognition, and data visualization ; Chapter 19. Statistical visualization of big data through hadoop streaming in rstudio ; Chapter 20. Visualization of big data sets using computer graphics ; Chapter 21. Visualization of predictive modeling for big data using various approaches when there are rare events at differing levels ; Chapter 22. Introduction to smart city and agricultural revolution: big data and internet of things (IoT) ; Chapter 23. Mining multimodal big data: tensor methods and applications -- Section 7. Applications of big data visualization. Chapter 24. Big data and its role in facilitating the visualization of financial analytics ; Chapter 25. Visualization and storage of big data for linguistic applications ; Chapter 26. Big data analysis techniques for visualization of genomics in medicinal plants ; Chapter 27. The artist's move: the discipline of dance and big data ; Chapter 28. Visualizing big data from a philosophical perspective ; Chapter 29. Big data analytics and visualization of performance of Stock exchange companies based on balanced scorecard indicators ; Chapter 30. Visualization tools for big data analytics in quantitative chemical analysis: a tutorial in chemometrics. | |
| 506 | |a Restricted to subscribers or individual electronic text purchasers. | ||
| 520 | 3 | |a "This book presents the concepts of big data, explores its analytics and technologies and their applications and develops an understanding of issues pertaining to the use of big data in multidisciplinary fields. It explores big data through the historical and technical background, architecture, open-source and commercial programming systems, analytics, state of practice in industry, and other topics"-- |c Provided by publisher. | |
| 530 | |a Also available in print. | ||
| 538 | |a Mode of access: World Wide Web. | ||
| 588 | 0 | |a Description based on title screen (IGI Global, viewed 02/08/2018). | |
| 650 | 0 | |a Big data |v Handbooks, manuals, etc. | |
| 650 | 0 | |a Information visualization, |v Handbooks, manuals, etc. | |
| 653 | |a Analytics. | ||
| 653 | |a Architecture Patterns. | ||
| 653 | |a Clouds and Clusters. | ||
| 653 | |a Computational Business Intelligence. | ||
| 653 | |a Computational Energy. | ||
| 653 | |a Programming Systems. | ||
| 653 | |a Technologies. | ||
| 700 | 1 | |a Cook, Jeffrey S. |d 1966- |e editor. | |
| 700 | 1 | |a Segall, Richard |d 1949- |e editor. | |
| 710 | 2 | |a IGI Global, |e publisher. | |
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| contents | Volume I. Section 1. Introduction to big data and storage systems. Chapter 1. Overview of big data and its visualization ; Chapter 2. Overview of big-data-intensive storage and its technologies -- Section 2. Big data technologies and architectural patterns. Chapter 3. Database systems for big data storage and retrieval ; Chapter 4. Hadoop framework for handling big data needs ; Chapter 5. Role of open source software in big data storage -- Section 3. Big data in clouds, clusters, and grids. Chapter 6. Big data tools for computing on clouds and grids ; Chapter 7. A review of security challenges in cloud storage of big data ; Chapter 8. Architecture for big data storage in different cloud deployment models -- Section 4. Big data processing for storage and visualization. Chapter 9. Programming and pre-processing systems for big data storage and visualization ; Chapter 10. High performance storage for big data analytics and visualization ; Chapter 11. Big data in massive parallel processing: a multi-core processors perspective ; Chapter 12. Distributed streaming big data analytics for internet of things (IoT) -- Section 5. Applications of big data storage. Chapter 13. Scalable data warehouse architecture: a higher education case study ; Chapter 14. Resource provisioning and scheduling of big data processing jobs ; Chapter 15. Issues and methods for access, storage, and analysis of data from online social communities ; Chapter 16. Big data storage for the modeling of historical time series solar irradiations -- Volume II. Section 6. Visualization tools and techniques. Chapter 17. Big data visualization tools and techniques ; Chapter 18. The image as big data toolkit: an application case study in image analysis, feature recognition, and data visualization ; Chapter 19. Statistical visualization of big data through hadoop streaming in rstudio ; Chapter 20. Visualization of big data sets using computer graphics ; Chapter 21. Visualization of predictive modeling for big data using various approaches when there are rare events at differing levels ; Chapter 22. Introduction to smart city and agricultural revolution: big data and internet of things (IoT) ; Chapter 23. Mining multimodal big data: tensor methods and applications -- Section 7. Applications of big data visualization. Chapter 24. Big data and its role in facilitating the visualization of financial analytics ; Chapter 25. Visualization and storage of big data for linguistic applications ; Chapter 26. Big data analysis techniques for visualization of genomics in medicinal plants ; Chapter 27. The artist's move: the discipline of dance and big data ; Chapter 28. Visualizing big data from a philosophical perspective ; Chapter 29. Big data analytics and visualization of performance of Stock exchange companies based on balanced scorecard indicators ; Chapter 30. Visualization tools for big data analytics in quantitative chemical analysis: a tutorial in chemometrics. |
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| discipline | Informatik |
| format | Electronic eBook |
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| id | ZDB-98-IGB-00179829 |
| illustrated | Not Illustrated |
| indexdate | 2025-03-18T14:30:29Z |
| institution | BVB |
| isbn | 9781522531432 |
| language | English |
| oclc_num | 1022575719 |
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| spelling | Handbook of research on big data storage and visualization techniques Richard S. Segall and Jeffrey S. Cook, editors. Big data storage and visualization techniques Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) IGI Global [c2018] 46 PDFs (2 volumes) text rdacontent electronic isbdmedia online resource rdacarrier Includes bibliographical references and index. Volume I. Section 1. Introduction to big data and storage systems. Chapter 1. Overview of big data and its visualization ; Chapter 2. Overview of big-data-intensive storage and its technologies -- Section 2. Big data technologies and architectural patterns. Chapter 3. Database systems for big data storage and retrieval ; Chapter 4. Hadoop framework for handling big data needs ; Chapter 5. Role of open source software in big data storage -- Section 3. Big data in clouds, clusters, and grids. Chapter 6. Big data tools for computing on clouds and grids ; Chapter 7. A review of security challenges in cloud storage of big data ; Chapter 8. Architecture for big data storage in different cloud deployment models -- Section 4. Big data processing for storage and visualization. Chapter 9. Programming and pre-processing systems for big data storage and visualization ; Chapter 10. High performance storage for big data analytics and visualization ; Chapter 11. Big data in massive parallel processing: a multi-core processors perspective ; Chapter 12. Distributed streaming big data analytics for internet of things (IoT) -- Section 5. Applications of big data storage. Chapter 13. Scalable data warehouse architecture: a higher education case study ; Chapter 14. Resource provisioning and scheduling of big data processing jobs ; Chapter 15. Issues and methods for access, storage, and analysis of data from online social communities ; Chapter 16. Big data storage for the modeling of historical time series solar irradiations -- Volume II. Section 6. Visualization tools and techniques. Chapter 17. Big data visualization tools and techniques ; Chapter 18. The image as big data toolkit: an application case study in image analysis, feature recognition, and data visualization ; Chapter 19. Statistical visualization of big data through hadoop streaming in rstudio ; Chapter 20. Visualization of big data sets using computer graphics ; Chapter 21. Visualization of predictive modeling for big data using various approaches when there are rare events at differing levels ; Chapter 22. Introduction to smart city and agricultural revolution: big data and internet of things (IoT) ; Chapter 23. Mining multimodal big data: tensor methods and applications -- Section 7. Applications of big data visualization. Chapter 24. Big data and its role in facilitating the visualization of financial analytics ; Chapter 25. Visualization and storage of big data for linguistic applications ; Chapter 26. Big data analysis techniques for visualization of genomics in medicinal plants ; Chapter 27. The artist's move: the discipline of dance and big data ; Chapter 28. Visualizing big data from a philosophical perspective ; Chapter 29. Big data analytics and visualization of performance of Stock exchange companies based on balanced scorecard indicators ; Chapter 30. Visualization tools for big data analytics in quantitative chemical analysis: a tutorial in chemometrics. Restricted to subscribers or individual electronic text purchasers. "This book presents the concepts of big data, explores its analytics and technologies and their applications and develops an understanding of issues pertaining to the use of big data in multidisciplinary fields. It explores big data through the historical and technical background, architecture, open-source and commercial programming systems, analytics, state of practice in industry, and other topics"-- Provided by publisher. Also available in print. Mode of access: World Wide Web. Description based on title screen (IGI Global, viewed 02/08/2018). Big data Handbooks, manuals, etc. Information visualization, Handbooks, manuals, etc. Analytics. Architecture Patterns. Clouds and Clusters. Computational Business Intelligence. Computational Energy. Programming Systems. Technologies. Cook, Jeffrey S. 1966- editor. Segall, Richard 1949- editor. IGI Global, publisher. (Original) (DLC)2017016107 Print version: 1522531424 9781522531425 (DLC) 2017016107 |
| spellingShingle | Handbook of research on big data storage and visualization techniques Volume I. Section 1. Introduction to big data and storage systems. Chapter 1. Overview of big data and its visualization ; Chapter 2. Overview of big-data-intensive storage and its technologies -- Section 2. Big data technologies and architectural patterns. Chapter 3. Database systems for big data storage and retrieval ; Chapter 4. Hadoop framework for handling big data needs ; Chapter 5. Role of open source software in big data storage -- Section 3. Big data in clouds, clusters, and grids. Chapter 6. Big data tools for computing on clouds and grids ; Chapter 7. A review of security challenges in cloud storage of big data ; Chapter 8. Architecture for big data storage in different cloud deployment models -- Section 4. Big data processing for storage and visualization. Chapter 9. Programming and pre-processing systems for big data storage and visualization ; Chapter 10. High performance storage for big data analytics and visualization ; Chapter 11. Big data in massive parallel processing: a multi-core processors perspective ; Chapter 12. Distributed streaming big data analytics for internet of things (IoT) -- Section 5. Applications of big data storage. Chapter 13. Scalable data warehouse architecture: a higher education case study ; Chapter 14. Resource provisioning and scheduling of big data processing jobs ; Chapter 15. Issues and methods for access, storage, and analysis of data from online social communities ; Chapter 16. Big data storage for the modeling of historical time series solar irradiations -- Volume II. Section 6. Visualization tools and techniques. Chapter 17. Big data visualization tools and techniques ; Chapter 18. The image as big data toolkit: an application case study in image analysis, feature recognition, and data visualization ; Chapter 19. Statistical visualization of big data through hadoop streaming in rstudio ; Chapter 20. Visualization of big data sets using computer graphics ; Chapter 21. Visualization of predictive modeling for big data using various approaches when there are rare events at differing levels ; Chapter 22. Introduction to smart city and agricultural revolution: big data and internet of things (IoT) ; Chapter 23. Mining multimodal big data: tensor methods and applications -- Section 7. Applications of big data visualization. Chapter 24. Big data and its role in facilitating the visualization of financial analytics ; Chapter 25. Visualization and storage of big data for linguistic applications ; Chapter 26. Big data analysis techniques for visualization of genomics in medicinal plants ; Chapter 27. The artist's move: the discipline of dance and big data ; Chapter 28. Visualizing big data from a philosophical perspective ; Chapter 29. Big data analytics and visualization of performance of Stock exchange companies based on balanced scorecard indicators ; Chapter 30. Visualization tools for big data analytics in quantitative chemical analysis: a tutorial in chemometrics. Big data Handbooks, manuals, etc. Information visualization, Handbooks, manuals, etc. |
| title | Handbook of research on big data storage and visualization techniques |
| title_alt | Big data storage and visualization techniques |
| title_auth | Handbook of research on big data storage and visualization techniques |
| title_exact_search | Handbook of research on big data storage and visualization techniques |
| title_full | Handbook of research on big data storage and visualization techniques Richard S. Segall and Jeffrey S. Cook, editors. |
| title_fullStr | Handbook of research on big data storage and visualization techniques Richard S. Segall and Jeffrey S. Cook, editors. |
| title_full_unstemmed | Handbook of research on big data storage and visualization techniques Richard S. Segall and Jeffrey S. Cook, editors. |
| title_short | Handbook of research on big data storage and visualization techniques |
| title_sort | handbook of research on big data storage and visualization techniques |
| topic | Big data Handbooks, manuals, etc. Information visualization, Handbooks, manuals, etc. |
| topic_facet | Big data Handbooks, manuals, etc. Information visualization, Handbooks, manuals, etc. |
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