SCE Library
  • Lists
    Public lists PGDE Programme PgCCP PgCHE M.Ed (Science) New Books on Mindfulness New List Books donated by Bhutan Society for the UK Trust Fund Books Donated by Consulate General of India Phuentsholing PGCERT New List 2023 View all
    Your lists Log in to create your own lists
  • Log in to your account
  • Your cookies
  • Search history
  • Clear

About Us
Library Rules
Membership
Collection
Code of Conduct
  • Advanced search
  • Course reserves
  • Tag cloud
  • Libraries
  • Log in to your account

    1. Home
    2. Details for: Essentials of Business Analytics An Introduction to the Methodology and its Applications /
    Amazon cover image
    Image from Amazon.com
    Normal view MARC view ISBD view

    Essentials of Business Analytics [electronic resource] : An Introduction to the Methodology and its Applications / edited by Bhimasankaram Pochiraju, Sridhar Seshadri.

    Contributor(s):
    • Pochiraju, Bhimasankaram [editor.]
    • Seshadri, Sridhar [editor.]
    • SpringerLink (Online service)
    Material type: TextTextSeries: International Series in Operations Research & Management Science ; 264Publisher: Cham : Springer International Publishing : Imprint: Springer, 2019Edition: 1st ed. 2019Description: XVI, 980 p. 278 illus., 191 illus. in color. online resourceContent type:
    • text
    Media type:
    • computer
    Carrier type:
    • online resource
    ISBN:
    • 9783319688374
    Subject(s):
    • Operations research
    • Decision making
    • Statistics 
    • Big data
    • Operations Research/Decision Theory
    • Statistics for Business, Management, Economics, Finance, Insurance
    • Big Data/Analytics
    Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:
    • 658.40301 23
    LOC classification:
    • HD30.23
    Online resources:
    • Click here to access online
    Contents:
    Chapter 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.-.
    In: Springer eBooksSummary: This 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.
    Tags from this library: No tags from this library for this title. Log in to add tags.
    Star ratings
        Cancel rating. Average rating: 0.0 (0 votes)
    • Holdings ( 0 )
    • Title notes ( 2 )
    • Comments ( 0 )
    No physical items for this record

    Chapter 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.-.

    This 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.

    There are no comments on this title.

    Log in to your account to post a comment.
    • Print
    • Save record
      BIBTEX Dublin Core MARCXML MARC (non-Unicode/MARC-8) MARC (Unicode/UTF-8) MARC (Unicode/UTF-8, Standard) MODS (XML) RIS
    • More searches
      Search for this title in:
      Other Libraries (WorldCat) Other Databases (Google Scholar) Online Stores (Bookfinder.com) ebook (library genesis)

    Exporting to Dublin Core...




    Share
    Visit web site
    Maintained by Academic Resource Center, Samtse College of Education