Strategic System Assurance and Business Analytics

  • P. K. Kapur
  • Ompal Singh
  • Sunil Kumar Khatri
  • Ajit Kumar Verma

Part of the Asset Analytics book series (ASAN)

Table of contents

  1. Front Matter
    Pages i-xix
  2. Anish Gupta, Manish Gupta, Prateek Chaturvedi
    Pages 1-9
  3. Uday Kumar, Ajit Kumar Verma, Piyush Pratim Das
    Pages 37-44
  4. Pradnya Vishwas Chitrao, Rajiv Divekar, Sanchari Debgupta
    Pages 99-107
  5. Kapil Kumar Bansal, Mukesh K. Sharma, Dhowmya Bhatt
    Pages 155-161
  6. Sukhpal Kaur, Madhuchanda Rakshit
    Pages 187-200
  7. Sameer Tripathi, Samraddh Shukla, Shivam Attrey, Amit Agrawal, Vikas Singh Bhadoria
    Pages 245-254
  8. Shital Jhunjhunwala, Prasanna Vaidya
    Pages 275-285
  9. Pushpendra Kumar Verma, Preety
    Pages 303-314
  10. Sonal Tuteja, Rajeev Kumar
    Pages 407-417
  11. Alok Nikhil Jha, Geetam Tiwari, Niladri Chatterjee
    Pages 419-443
  12. Yury S. Klochkov, Albina Gazizulina, Maria Ostapenko
    Pages 445-460
  13. Ritu Bibyan, Sameer Anand, Ajay Jaiswal
    Pages 491-502
  14. Charu Virmani, Tanu Choudhary
    Pages 517-528
  15. H. N. Suresh, N. Madhusudan, D. Sarvana Bavan, B. S. Murgayya
    Pages 543-556
  16. Chetanya Batra, Gandharv Pathak, Siddharth Gupta, Saurabh Singh, Chetna Gupta, Varun Gupta
    Pages 557-562
  17. Omar H. Alhazmi
    Pages 579-587
  18. Rohit Khatri, Diana Denice, Manoj Kumar
    Pages 589-602

About this book


This book systematically examines and quantifies industrial problems by assessing the complexity and safety of large systems. It includes chapters on system performance management, software reliability assessment, testing, quality management, analysis using soft computing techniques, management analytics, and business analytics, with a clear focus on exploring real-world business issues. Through contributions from researchers working in the area of performance, management, and business analytics, it explores the development of new methods and approaches to improve business by gaining knowledge from bulk data. With system performance analytics, companies are now able to drive performance and provide actionable insights for each level and for every role using key indicators, generate mobile-enabled scorecards, time series-based analysis using charts, and dashboards.

In the current dynamic environment, a viable tool known as multi-criteria decision analysis (MCDA) is increasingly being adopted to deal with complex business decisions. MCDA is an important decision support tool for analyzing goals and providing optimal solutions and alternatives. It comprises several distinct techniques, which are implemented by specialized decision-making packages. This book addresses a number of important MCDA methods, such as DEMATEL, TOPSIS, AHP, MAUT, and Intuitionistic Fuzzy MCDM, which make it possible to derive maximum utility in the area of analytics. As such, it is a valuable resource for researchers and academicians, as well as practitioners and business experts.


Management Analytics Performance Analytics Reliability Quality Management Big Data Analytics

Editors and affiliations

  • P. K. Kapur
    • 1
  • Ompal Singh
    • 2
  • Sunil Kumar Khatri
    • 3
  • Ajit Kumar Verma
    • 4
  1. 1.Amity Center for Interdisciplinary ResearchAmity UniversityNoidaIndia
  2. 2.Department of Operational ResearchUniversity of DelhiNew DelhiIndia
  3. 3.Amity UniversityTashkentUzbekistan
  4. 4.Western Norway University of Applied SciencesHaugesundNorway

Bibliographic information

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