Handbook of big data reasearch methods / edited by Shahriar Akter and Samuel Fosso Wamba.
Material type:
TextLanguage: English Series: Research handbooks in information systemsPublication details: Cheltenham ; Northampton : Edward Elgar, 2023.Description: 1 online resourceContent type: - text
- computer
- online resource
- 005.7
| Item type | Current library | Call number | URL | Status | Notes | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|---|---|
Ebook - EBSCO
|
CYA Library Ebook Available Online | 005.7 BIG (Browse shelf(Opens below)) | Link to resource | Available | Access through the CYA network or with a u/p from the librarian. |
Includes bibliographical references and index.
1. Introduction to the Handbook of Big Data Research Methods -- 2. Big data research methods in financial prediction -- 3. Big data, data analytics and artificial intelligence in accounting: an overview -- 4. The benefits of marketing analytics and challenges -- 5. How big data analytics will transform the future of fashion retailing -- 67. Descriptive analytics and data visualization in e-commerce -- 7. Application of big data Bayesian interrupted time-series modeling for intervention analysis -- 8. How predictive analytics can empower your decision making --9. Gaussian process classification for psychophysical detection tasks in multiple populations (wide big data) using transfer learning -- 10. Predictive analytics for machine learning and deep learning -- 11. Building a successful data science ecosystem using public cloud -- 12. How HR analytics can leverage big data to minimise employees' exploitation and promote their welfare for sustainable competitive advantage -- 13. Embracing data-driven analytics (DDA) in human resource management to measure the organization performance -- 14. A process framework for big data research: social network analysis using design science -- 15. Notre-Dame de Paris cathedral is burning: let's turn to Twitter -- 16. Does personal data protection matter in data protection law? A transformational model to fit in the digital era -- 17. Understanding the future trends and innovations of AI-based CRM systems -- Descriptive analytics methods in big data: a systematic literature review.