Applied Big Data Analytics in Operations Management

Applied Big Data Analytics in Operations Management

Indexed In: SCOPUS
Release Date: September, 2016|Copyright: © 2017 |Pages: 251
DOI: 10.4018/978-1-5225-0886-1
ISBN13: 9781522508861|ISBN10: 1522508864|EISBN13: 9781522508878
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Description & Coverage
Description:

Operations management is a tool by which companies can effectively meet customers’ needs using the least amount of resources necessary. With the emergence of sensors and smart metering, big data is becoming an intrinsic part of modern operations management.

Applied Big Data Analytics in Operations Management enumerates the challenges and creative solutions and tools to apply when using big data in operations management. Outlining revolutionary concepts and applications that help businesses predict customer behavior along with applications of artificial neural networks, predictive analytics, and opinion mining on business management, this comprehensive publication is ideal for IT professionals, software engineers, business professionals, managers, and students of management.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Business Analytics
  • Customer-Centric Business
  • Educational Systems
  • Maintenance Data
  • Neural Networks
  • Opinion Mining
  • Predictive Analytics
  • Semi-Structured Data
Reviews & Statements

Computer scientists along with engineers in several fields address various challenges in operation management and how to overcome them using big data analytics. Among their topics are applying artificial neural networks in predicting the degradation of tram tracks using maintenance data, predictive analytics in operations management, pros and cons of applying opinion mining on operations management: a big data perspective, a conceptual framework for managing the operation of an educational system synchronous with a big data approach, managing semi-structured data of small and medium companies using semantic techniques, and big data security with a Hadoop framework.

– Protoview Reviews
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Editor/Author Biographies
Manish Kumar received his PhD degree on Data Management in Wireless Sensor Networks from Indian Institute of Information Technology, Allahabad India in 2011. He received his M.Tech in Computer Science from Birla Institute of Technology, Mesra (Ranchi) India. He is a professional member of IEEE and ACM. Currently he is working as an Assistant Professor in Department of Information Technology at Indian Institute of Information Technology, Allahabad India. His research interest includes data mining and warehousing, data management in wireless sensor networks and big data analytics. He has contributed in a number of books in the same areas and has many national and international publications in renowned journals and conferences.
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