Research anthology on big data analytics, architectures, and applications / Information Resources Management Association, editor.

Format:

Book

Contributor:

Information Resources Management Association, editor.

Association,, Information Resources Management, editor.

Language:

English

Subjects (All):

Big data.

Quantitative research.

Physical Description:

108 PDFs (4 volumes (1988 pages))

Place of Publication:

Hershey, Pennsylvania : Engineering Science Reference, [2022]

System Details:

Mode of access: World Wide Web.

Summary:

"This complete reference source on big data analytics that offers the latest, innovative architectures and frameworks, as well as explores a variety of applications within various industries offering an international perspective on a variety of topics such as advertising curricula, driven supply chain, and smart cities"

Contents:

Volume I. Section 1. Fundamental concepts and theories. Chapter 1. Understanding big data ; Chapter 2. Overview of big data and its visualization ; Chapter 3. Introduction of big data with analytics of big data ; Chapter 4. Introduction to big data and business analytics ; Chapter 5. What is open source software (OSS) and what is big data? ; Chapter 6. Healthcare big data: a comprehensive overview ; Chapter 7. A brief survey on big data in healthcare

Section 2. Development and design methodologies. Chapter 8. Big data analytics and models ; Chapter 9. Developing a method to valuate the collection of big data ; Chapter 10. Big-data-based architectures and techniques: big data reference architecture ; Chapter 11. Big data analytics in cloud computing: effective deployment of data analytics tools ; Chapter 12. Decision framework for engaging cloud-based big data analytics vendors ; Chapter 13. Big data and high-performance analyses and processes ; Chapter 14. A conceptual model for describing the integration of decision aspect into big data ; Chapter 15. Toward a conceptualization of big data value chain: from business problems to value creation ; Chapter 16. Role of big data in Internet of things networks ; Chapter 17. Big data analytics and IoT in smart city applications ; Chapter 18. Integrating blockchain platforms with big data solutions for regional innovation development ; Chapter 19. Big data in railway om: a dependability approach ; Chapter 20. Usage and analysis of big data in e-health domain ; Chapter 21. Intelligent techniques for analysis of big data about healthcare and medical records ; Chapter 22. Evolution of big data in medical imaging modalities to extract features using region growing segmentation, GLCM, and discrete wavelet transform ; Chapter 23. A framework for effective data analytics for tourism sector: big data approach

Volume II. Chapter 24. Building high quality big data-based applications in supply chains ; Chapter 25. Big data analytics and visualization for food health status determination using bigmart data

Section 3. Tools and technologies. Chapter 26. Big data and advance analytics: architecture, techniques, applications, and challenges ; Chapter 27. Big data and digital analytics ; Chapter 28. Big data visualization tools and techniques ; Chapter 29. Big data analytics tools and platform in big data landscape ; Chapter 30. Statistical and computational needs for big data challenges ; Chapter 31. A survey of big data analytics using machine learning algorithms ; Chapter 32. Big data analytics with machine learning and deep learning methods for detection of anomalies in network traffic ; Chapter 33. Big data analytics and mining for knowledge discovery ; Chapter 34. Distributed streaming big data analytics for Internet of things (IoT) ; Chapter 35. Statistical visualization of big data through hadoop streaming in Rstudio ; Chapter 36. Intelligent information system for academic institutions: using big data analytic approach ; Chapter 37. Big data and digital tools applied to the teaching: learning in graduate programs in Mexico ; Chapter 38. From business intelligence to big data: the power of analytics ; Chapter 39. Big data and enterprise applications ; Chapter 40. A service-oriented foundation for big data ; Chapter 41. Customer analytics capabilities in the big data spectrum: a systematic approach to achieve sustainable firm performance ; Chapter 42. Social media big data analytics for demand forecasting: development and case implementation of an innovative framework ; Chapter 43. Using big data analytics to forecast trade volumes in global supply chain management ; Chapter 44. Efficient big data-based storage and processing model in Internet of things for improving accuracy fault detection in industrial processes ; Chapter 45. Application of big data in digital epidemiology ; Chapter 46. Big data analytics using apache hive to analyze health data

Volume III. Chapter 47. Big data analytics in healthcare sector ; Chapter 48. Big data applications in healthcare administration ; Chapter 49. Big data, data mining, and data analytics in IoT-based healthcare applications ; Chapter 50. Remote patient monitoring for healthcare: a big challenge for big data ; Chapter 51. ANT perspective of healthcare big data for service delivery in South Africa ; Chapter 52. Applications of big data and green IoT-enabling technologies for smart cities ; Chapter 53. Big data for satellite image processing: analytics, tools, modeling, and challenges

Section 4. Utilization and applications. Chapter 54. An analysis of big data analytics ; Chapter 55. Insight into big data analytics: challenges, recent trends, and future prospects ; Chapter 56. A study of big data processing for sentiments analysis ; Chapter 57. Big data for prediction: patent analysis patenting big data for prediction analysis ; Chapter 58. The impact of big data analytics and challenges to cyber security ; Chapter 59. Big data analytics adoption factors in improving information systems security ; Chapter 60. Big data and global software engineering ; Chapter 61. Big data analytics in higher education ; Chapter 62. Implementation of big data analytics for government enterprise ; Chapter 63. Public administration curriculum-based big data policy-analytic epistemology: symbolic IoT action-learning solution model ; Chapter 64. Bootstrapping urban planning: addressing big data issues in smart cities ; Chapter 65. Big data, data management, and business intelligence ; Chapter 66. The use of big data in marketing analytics ; Chapter 67. Use of big data analytics by tax authorities ; Chapter 68. Big data analytics driven supply chain transformation ; Chapter 69. Exploring factors influencing big data and analytics adoption in healthcare management ; Chapter 70. An article on big data analytics in healthcare applications and challenges ; Chapter 71. Big data classification and Internet of things in healthcare

Volume IV. Chapter 72. Computational and data mining perspectives on HIV/AIDS in big data era: opportunities, challenges, and future directions

Section 5. Organizational and social implications. Chapter 73. Big data and IoT applications in real life environment ; Chapter 74. Amelioration of big data analytics by employing big data tools and techniques ; Chapter 75. Understanding the determinants of big data analytics adoption ; Chapter 76. Human-computer interaction with big data analytics ; Chapter 77. The components of big data and knowledge management will change radically how people collaborate and develop complex research ; Chapter 78. Data management and big data analytics: data management in digital economy ; Chapter 79. Importance of big data and hadoop in e-servicing ; Chapter 80. Improving forecasting for customer service supply chain using big data analytics ; Chapter 81. Intelligent big data analytics in health ; Chapter 82. The strengths, weaknesses, opportunities, and threats analysis of big data analytics in healthcare ; Chapter 83. Cloud computing big data adoption impacts on teaching and learning in higher education: a systematic review

Section 6. Managerial impact. Chapter 84. Big data technologies and management ; Chapter 85. Managerial controversies in artificial intelligence and big data analytics ; Chapter 86. Improving project management decisions with big data analytics ; Chapter 87. Management of big data projects: PMI approach for success ; Chapter 88. Big data analytics in supply chain management ; Chapter 89. Big data adoption: a comparative study of the Indian manufacturing and services sectors ; Chapter 90. Exploring big data analytic approaches to cancer blog text analysis

Section 7. Critical issues and challenges. Chapter 91. A survey on comparison of performance analysis on a cloud-based big data framework ; Chapter 92. Fast data vs.

big data with IoT streaming analytics and the future applications ; Chapter 93. Integration of data mining and business intelligence in big data analytics: a research agenda on scholarly publications ; Chapter 94. Mapping the intellectual structure of the big data research in the IS discipline: a citation/co-citation analysis ; Chapter 95. Big data analytics in undergraduate advertising curricula: a global survey of higher education institutions ; Chapter 96. How big data transforms manufacturing industry: a review paper.

Notes:

Description based on print version record.

Includes bibliographical references and index.

ISBN:

9781668436639

OCLC:

1281988850