Data Driven Decision Making using Analytics (eBook, ePUB)

Redaktion: Gandhi, Parul; Dev, Kapal; Bhatia, Surbhi

• Format: ePub

Produktbeschreibung

This book aims to explain Data Analytics towards decision making in terms of models and algorithms, theoretical concepts, applications, experiments in relevant domains or focused on specific issues. It explores the concepts of database technology, machine learning, knowledge-based system, high performance computing, information retrieval, finding patterns hidden in large datasets and data visualization. Also, it presents various paradigms including pattern mining, clustering, classification, and data analysis. Overall aim is to provide technical solutions in the field of data analytics and data mining.

Features:

• Covers descriptive statistics with respect to predictive analytics and business analytics.
• Discusses different data analytics platforms for real-time applications.
• Explain SMART business models.
• Includes algorithms in data sciences alongwith automated methods and models.
• Explores varied challenges encountered by researchers and businesses in the realm of real-time analytics.

This book aims at researchers and graduate students in data analytics, data sciences, data mining, and signal processing.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 150
• Erscheinungstermin: 16. Dezember 2021
• Englisch
• ISBN-13: 9781000506495
• Artikelnr.: 62861341

Autorenporträt

Dr. Parul Gandhi A Doctorate in the subject of Computer Science with the study area in Software Engineering from Guru Jambheshwar University, Hisar. She is also a Gold Medalist in M.Sc. Computer Science. She is having a strong inclination towards academics and research. She has 15 yrs of academic, research and administrative experiences. She has published more than 40 research papers in reputed International/ National journal and conferences. Her research interests include software Quality, soft computing, and Software metrics and Component Based Software Development , Data Mining, IOT. Presently she is working as Professor, Manav Rachna International Institute of Research and Studies(MRIIRS), Faridabad. She is also handling the PhD program of the University. She has also been associated as a Editorial Board members of SN Applied Sciences and also a reviewer with various reputed journals of IEEE and Conferences. She has successfully published many book chapters in scopus indexed books and also editing various books with high indexing databases like Wiley and Springer. She is also handling special issues in journals of Elsevier, Springer as a guest editor. She has been called as a resource person in various FDPs and also chaired session in various IEEE conferences. She is the life time member of Computer Society of India. Dr. Surbhi Bhatia PMP® A doctorate in Computer Science and Engineering from Banasthali Vidypaith, India. She is currently an Assistant Professor in Department of Information Systems, College of Computer Sciences and Information Technology, King Faisal University, Saudi Arabia. She has rich 8 years of teaching and academic experience. She is in the Editorial board member with Inderscience Publishers in the International Journal of Hybrid Intelligence, SN Applied Sciences, Springer and also in several IEEE conferences. She has been granted seven national and international patents. She has published more than 30 papers in reputed journals and conferences in high indexing databases including SCI, SCIE, Web of Science and Scopus. She has delivered talks as keynote speaker in IEEE conferences and in faculty development programs. She has successfully authored two books from Springer and Wiley. Currently, she is editing three books from CRC Press, Elsevier and Springer. She is also handling special issues in journals of Elsevier, Springer as a guest editor. She has been an active researcher in the field of Data mining, Machine Learning, and Information Retrieval. Dr. Kapal Dev Post-doctral Research Fellow with the CONNECT Centre, School of Computer Science and Statistics, Trinity College Dublin (TCD). His education Profile revolves over ICT background i.e. Electronics (B.E and M.E), Telecommunication Engineering (PhD) and Post-doc (Fusion of 5G and Blockchain). He was awarded the PhD degree by Politecnico di Milano, Italy in July 2019. His research interests include Blockchain, 5G Beyond Networks and Artificial Intelligence. Previously, he worked as 5G Junior Consultant and Engineer at Altran Italia S.p.A, Milan on 5G use cases. He is PI of two Erasmus + International Credit Mobility projects. He is evaluator of MSCA Co-Fund schemes, Elsevier Book proposals and top scientific journals and conferences including IEEE TII, IEEE TITS, IEEE TNSE, IEEE JBHI, FGCS, COMNET, TETT, IEEE VTC, WF-IoT. TPC member of IEEE BCA 2020 in conjunction with AICCSA 2020, ICBC 2021, DICG Colocated with Middleware 2020 and FTNCT 2020. He is also serving as GE in COMNET (I.F 3.11), Associate Editor in IET Quantum Communication, GE in COMCOM (I.F: 2.8), GE in CMC-Computers, Materials & Continua (I.F 4.89) and lead chair in one of CCNC 2021 workshops. He is also acting as Head of Projects for Oceans Network funded by European Commission.

Inhaltsangabe

1. Securing big data using big data mining. 2. Analytical Theory: Frequent
Pattern Mining. 3. A Journey from Big Data To Data Mining In Quality
Improvement. 4. Significance Of Data Mining In The Domain Of Intrusion
Detection. 5. Data Analytics and Mining: Platforms for Real-Time  
Applications. 6. Analysis of Government Policies to Control Pandemic and
its affects on Climate Change to improve Decision Making. 7. Data Analytics
and Data Mining strategy to improve Quality, Performance and decision
making. 8. SMART Business Model -An analytical approach to astute Data
Mining for Successful Organization. 9. AI and Healthcare: Praiseworthy
aspects and Shortcomings