Big Data Management and AnalyticsWith the proliferation of information, big data management and analysis have become an indispensable part of any system to handle such amounts of data. The amount of data generated by the multitude of interconnected devices increases exponentially, making the storage and processing of these data a real challenge.Big data management and analytics have gained momentum in almost every industry, ranging from finance or healthcare. Big data can reveal key insights if handled and analyzed properly; it has great application potential to improve the working of any industry. This book covers the spectrum aspects of big data; from the preliminary level to specific case studies. It will help readers gain knowledge of the big data landscape.Highlights of the topics covered include description of the Big Data ecosystem; real-world instances of big data issues; how the Vs of Big Data (volume, velocity, variety, veracity, valence, and value) affect data collection, monitoring, storage, analysis, and reporting; structural process to get value out of Big Data and recognize the differences between a standard database management system and a big data management system.Readers will gain insights into choice of data models, data extraction, data integration to solve large data problems, data modelling using machine learning techniques, Spark’s scalable machine learning techniques, modeling a big data problem into a graph database and performing scalable analytical operations over the graph and different tools and techniques for processing big data and its applications including in healthcare and finance.Contents: Introduction to Big DataBig Data Management and ModelingBig Data ProcessingBig Data Analytics and Machine LearningBig Data Analytics Through VisualizationTaming Big Data with Spark 2.0Managing Big Data in Cloud StorageBig Data in HealthcareBig Data in FinanceEnabling Tools and Technologies for Big Data AnalyticsReferencesIndexReadership: Graduate and postgraduate students in Innovation/Technology/Knowledge/ Information Management. For researchers, this book provides fundamental and needful insights into the domain that can assist them in exploring this area from the elementary level. Industry CIOs will also find the book useful for conceptual clarity. ‘This book embarks on a data analysis journey, from foundational concepts to the deployment of advanced machine learning models, and equips you with the technical prowess to transform raw data into actionable intelligence.’ – Dr Elhadj BenkhelifaProfessor, School of Digital, Technologies and Arts & Founding Director of the Smart Systems, AI and Cybersecurity Research Centre, Staffordshire University, UK’This book explores the intricacies of data management and analytics in this in-depth guide, delving into data storage, processing, and advanced analytical techniques for a holistic understanding of data ecosystems.’ – Dr Dragan Perakovi’Professor and Head of Department of Information and Communication Traffic & Head of Chair of Information and Communication System and Service ManagementUniversity of Zagreb, Croatia’This title masters the technical intricacies of data analysis, from optimizing data processing pipelines with distributed computing frameworks to implementing cutting-edge machine learning algorithms, and unlocks the true potential of your data assets.’ – Dr Kwok Tai ChuiAssistant Professor, Electronic Engineering and Computer ScienceHong Kong Metropolitan University (HKMU), Hong Kong Key Features:This book describes the Big Data ecosystemIt includes real-world instances of big data issuesExplain how the Vs of Big Data (volume, velocity, variety, veracity, valence, and value) affect data collection, monitoring, storage, analysis, and reportingHow we can get value out of Big Data by following a structural process’Recognize the differences between a standard database management system and a big data management systemHow to choose a data model that fits your data’s properties’How to get data out of a database or a large data management system’Recognize when a large data problem necessitates data integrationExplore and prepare data for modelling using machine learning techniquesAnalysis of big data problems with Spark’s scalable machine learning techniquesModeling a big data problem into a graph database and performing scalable analytical operations over the graphDiscuss different tools and techniques for processing big dataBig data applications in healthcare and finance ISBN: 9789811257117, 9811257116
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