ABSTRACT

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.

chapter 2|15 pages

Analytical Theory

Frequent Pattern Mining

chapter 5|20 pages

Data Analytics and Mining

Platforms for Real-Time Applications

chapter 8|13 pages

SMART Business Model

An Analytical Approach to Astute Data Mining for Successful Organization

chapter 9|12 pages

AI and Healthcare

Praiseworthy Aspects and Shortcomings