Analytics : data science, data analysis and predictive analytics for business / Daniel Covington
Material type:
- 9781530135608
- HF 5415.3 .C68 2016

Item type | Current library | Home library | Collection | Call number | Copy number | Status | Date due | Barcode | |
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National University - Manila | LRC - Annex General Circulation | Gen. Ed - CEAS | GC HF 5415.3 .C68 2016 (Browse shelf(Opens below)) | c.1 | Available | NULIB000013475 |
Chapter 1. the importance of data in -- Chapter 2. big data -- Chapter 3. big data development -- Chapter 4. weighing the benefits and drawbacks of big data -- Chapter 5. benefits of big data to small businesses -- Chapter 6. key training for big data handling -- Chapter 7. process of data analysis -- Chapter 8. descriptive analysis -- Chapter 9. predictive analytics -- Chapter 10. predictive analysis -- Chapter 11. introducing r -- Chapter 12. why predictive analytics? -- Chapter 13. from descriptive to predictive analysis -- Chapter 14. critical success factors -- Chapter 15. what to expect -- Chapter 16. what is data science -- Chapter 17. further analysis of a data scientist's skills -- Chapter 18. big data impact to envisaged by 2020 -- Chapter 19. benefits of data science in the field of finance -- Chapter 20. how data science benefits retail -- Chapter 21. using big data in marketing -- Chapter 22. data science improving travel -- Chapter 23. big data and agriculture using big data to feed people -- Chapter 24 big data and law enforcement -- Chapter 25. use of big data in the public sector -- Chapter 26. big data and gaming -- Chapter 27. what about prescriptive analytics?.
What defines the success of a business? Is it the number of people employed by the firm? Is it the sales turnover of the business? Is it the strength of the customer base of the firm? Does employee satisfaction play a role in the success of business operation.
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