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Shulph Ink

Data Driven Decision Making using Analytics

Data Driven Decision Making using Analytics

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This book provides a comprehensive overview of Data Analytics, covering models, algorithms, theoretical concepts, applications, and experiments in various domains. It explores database technology, machine learning, knowledge-based systems, high-performance computing, information retrieval, pattern mining, clustering, classification, and data analysis. The aim is to provide technical solutions in data analytics and data mining, with a focus on real-time applications and SMART business models. It is suitable for researchers and graduate students in these fields.

Format: Hardback
Length: 138 pages
Publication date: 17 December 2021
Publisher: Taylor & Francis Ltd


This comprehensive book delves into the realm of data analytics, providing a comprehensive understanding of models, algorithms, theoretical concepts, applications, experiments, and relevant domains. It explores the intricate world of database technology, machine learning, knowledge-based systems, high-performance computing, information retrieval, pattern discovery in large datasets, and data visualization. Additionally, it presents various paradigms, including pattern mining, clustering, classification, and data analysis, aiming to offer technical solutions in the fields of data analytics and data mining.

The book encompasses a wide range of features, including descriptive statistics in predictive analytics and business analytics, discussions on diverse data analytics platforms for real-time applications, explanations of SMART business models, inclusion of algorithms in data sciences, and exploration of the challenges faced by researchers and businesses in the realm of real-time analytics.

Designed primarily for researchers and graduate students in data analytics, data sciences, data mining, and signal processing, this book serves as a valuable resource for those seeking to advance their knowledge and expertise in this rapidly evolving field.

Weight: 378g
Dimension: 160 x 241 x 17 (mm)
ISBN-13: 9781032058276

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