Data-driven decision-making using analytics

Table of contents: 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

The purpose of this book is to explain Data Analytics for decision making in terms of models and algorithms, theoretical principles, applications in relevant fields, and experiments centred on specific difficulties. It investigates database technology, machine learning, knowledge-based systems, high speed computing, information retrieval, identifying patterns disguised inside massive datasets, and data visualisation. In addition, various paradigms are discussed, including pattern mining, clustering, classification, and data analysis. The ultimate goal is to provide technology solutions for data analytics and data mining. Includes descriptive statistics for predictive and business analytics. It is discussed several data analytics systems for real-time applications. Describe the SMART organisational paradigms. Includes both data science algorithms and automated models and procedures. Examines the various challenges academics and corporations confront in the domain of real-time analytics. This book is written for academics and advanced students in the domains of data analytics, data sciences, data mining, and signal processing.