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020 _a9783319688374
_9978-3-319-68837-4
024 7 _a10.1007/978-3-319-68837-4
_2doi
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_2bicssc
072 7 _aBUS049000
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072 7 _aKJT
_2thema
072 7 _aKJMD
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082 0 4 _a658.40301
_223
245 1 0 _aEssentials of Business Analytics
_h[electronic resource] :
_bAn Introduction to the Methodology and its Applications /
_cedited by Bhimasankaram Pochiraju, Sridhar Seshadri.
250 _a1st ed. 2019.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2019.
300 _aXVI, 980 p. 278 illus., 191 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
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490 1 _aInternational Series in Operations Research & Management Science,
_x0884-8289 ;
_v264
505 0 _aChapter 1. Introduction -- Chapter 2. Data Collection -- Chapter 3. Data Management – Relational Database Systems (RDBMS) -- Chapter 4. Big Data Management -- Chapter 5. Data Visualization -- Chapter 6. Statistical Methods-Basic inferences -- Chapter 7. Statistical Methods-Regression -- Chapter 8. Advanced Regression Analysis -- Chapter 9. Text Analytics -- Chapter 10. Simulation -- Chapter 11. Introduction to Optimization -- Chapter 12. Forecasting Analytics -- Chapter 13. Count Data Regression -- Chapter 14. Survival Analysis -- Chapter 15. Machine Learning (Unsupervised) -- Chapter 16. Machine Learning (Supervised) -- Chapter 17. Deep Learning -- Chapter 18. Retail Analytics -- Chapter 19. Marketing Analytics -- Chapter 20. Financial Analytics -- Chapter 21. Social Media and Web Analytics -- Chapter 22. Healthcare Analytics -- Chapter 23. Pricing Analytics -- Chapter 24. Supply Chain Analytics -- Chapter 25. Case study: Ideal Insurance -- Chapter 26. Case study: AAA Airline -- Chapter 27. Case study: Informedia Solutions -- Chapter 28. Appendix 1: Introduction to R -- Chapter 29. Appendix 2: Introduction to Python -- Chapter 30. Appendix 3: Probability and Statistics.-.
520 _aThis comprehensive edited volume is the first of its kind, designed to serve as a textbook for long-duration business analytics programs. It can also be used as a guide to the field by practitioners. The book has contributions from experts in top universities and industry. The editors have taken extreme care to ensure continuity across the chapters. The material is organized into three parts: A) Tools, B) Models and C) Applications. In Part A, the tools used by business analysts are described in detail. In Part B, these tools are applied to construct models used to solve business problems. Part C contains detailed applications in various functional areas of business and several case studies. Supporting material can be found in the appendices that develop the pre-requisites for the main text. Every chapter has a business orientation. Typically, each chapter begins with the description of business problems that are transformed into data questions; and methodology is developed to solve these questions. Data analysis is conducted using widely used software, the output and results are clearly explained at each stage of development. These are finally transformed into a business solution. The companion website provides examples, data sets and sample code for each chapter.
650 0 _aOperations research.
650 0 _aDecision making.
650 0 _aStatistics .
650 0 _aBig data.
650 1 4 _aOperations Research/Decision Theory.
_0http://scigraph.springernature.com/things/product-market-codes/521000
650 2 4 _aStatistics for Business, Management, Economics, Finance, Insurance.
_0http://scigraph.springernature.com/things/product-market-codes/S17010
650 2 4 _aBig Data/Analytics.
_0http://scigraph.springernature.com/things/product-market-codes/522070
700 1 _aPochiraju, Bhimasankaram.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aSeshadri, Sridhar.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319688367
776 0 8 _iPrinted edition:
_z9783319688381
776 0 8 _iPrinted edition:
_z9783030447755
830 0 _aInternational Series in Operations Research & Management Science,
_x0884-8289 ;
_v264
856 4 0 _uhttps://doi.org/10.1007/978-3-319-68837-4
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