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Big Data Analytics in Bioinformatics and Healthcare

Big Data Analytics in Bioinformatics and Healthcare Book
Author : Baoying Wang,Ruowang Li,William Perrizo
Publisher : Unknown
Release : 2014-10
ISBN : 9781466666146
Language : En, Es, Fr & De

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Book Description :

"This book merges the fields of biology, technology, and medicine in order to present a comprehensive study on the emerging information processing applications necessary in the field of electronic medical record management"--

Big Data Analytics with Vehicle Data

Big Data Analytics with Vehicle Data Book
Author : Ashok Singamaneni
Publisher : Unknown
Release : 2016
ISBN : 9781369139341
Language : En, Es, Fr & De

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Book Description :

Many companies have invested a lot over the past decade just to collect the data and store them in a cloud. However collection of such large amount of data will be justified only when there are some useful insights drawn from them. There is a lot of data collected from vehicles. The volume, velocity, variability and complexity of the data from various sensors are massive. Access to this type of data is only going to increase with time, so industries need appropriate methods to transform this raw data into insights and knowledge. Extraction of insights which were previously unknown or potentially useful patterns or knowledge from this kind of these massive amounts of data can only be achieved by using Big Data analytics. Conventional software cannot handle the robustness of these, so modern tools such as Hadoop and Knime were used in this thesis to analyze the data. Raw high resolution data was used and a model was developed to understand vehicle/customer behaviors and then compared and contrasted. This thesis involves found a proper method for identifying and calculating the principal attributes that accurately and efficiently characterize a vehicle's operation. Predicting the power of new vehicles and finding the similarities between new vehicles and old vehicles was the main goal of this thesis.

Understanding Big Data Analytics for Enterprise Class Hadoop and Streaming Data

Understanding Big Data  Analytics for Enterprise Class Hadoop and Streaming Data Book
Author : Paul Zikopoulos,Chris Eaton
Publisher : McGraw Hill Professional
Release : 2011-10-22
ISBN : 0071790543
Language : En, Es, Fr & De

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Book Description :

Big Data represents a new era in data exploration and utilization, and IBM is uniquely positioned to help clients navigate this transformation. This book reveals how IBM is leveraging open source Big Data technology, infused with IBM technologies, to deliver a robust, secure, highly available, enterprise-class Big Data platform. The three defining characteristics of Big Data--volume, variety, and velocity--are discussed. You'll get a primer on Hadoop and how IBM is hardening it for the enterprise, and learn when to leverage IBM InfoSphere BigInsights (Big Data at rest) and IBM InfoSphere Streams (Big Data in motion) technologies. Industry use cases are also included in this practical guide. Learn how IBM hardens Hadoop for enterprise-class scalability and reliability Gain insight into IBM's unique in-motion and at-rest Big Data analytics platform Learn tips and tricks for Big Data use cases and solutions Get a quick Hadoop primer

BIG DATA ANALYTICS

BIG DATA ANALYTICS Book
Author : Raj Kamal,Preeti Saxena
Publisher : McGraw-Hill Education
Release : 2019-02-16
ISBN : 9353164974
Language : En, Es, Fr & De

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Book Description :

Big Data Analytics(BDA) is a rapidly evolving field that finds applications in many areas such as healthcare, medicine, advertising, marketing, and sales. This book dwells on all the aspects of Big Data Analytics and covers the subject in its entirety. It comprises several illustrations, sample codes, case studies and real-life analytics of datasets such as toys, chocolates, cars, and student’s GPAs. The book will serve the interests of undergraduate and post graduate students of computer science and engineering, information technology, and related disciplines. It will also be useful to software developers. Salient Features: - Comprehensive coverage on Big Data NoSQL Column-family, Object and Graph databases, programming with open-source Big Data - Hadoop and Spark ecosystem tools, such as MapReduce, Hive, Pig, Spark, Python, Mahout, Streaming, GraphX - Inclusion of latest topics machine learning, K-NN, predictive-analytics, similar and frequent item sets, clustering, decision-tree, classifiers recommenders, real-time streaming data analytics, graph networks, text, web structure, web-links, social network analytics. - Web supplement includes instructional PPT’s, solution of exercises, analysis using open source datasets of a car company, and topics for advanced learning.

Big Data Big Analytics

Big Data  Big Analytics Book
Author : Michael Minelli,Michele Chambers,Ambiga Dhiraj
Publisher : John Wiley & Sons
Release : 2012-12-27
ISBN : 1118239156
Language : En, Es, Fr & De

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Book Description :

Unique prospective on the big data analytics phenomenon for both business and IT professionals The availability of Big Data, low-cost commodity hardware and new information management and analytics software has produced a unique moment in the history of business. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. These capabilities are neither theoretical nor trivial. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue and profitability. The Age of Big Data is here, and these are truly revolutionary times. This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics. Learn more about the trends in big data and how they are impacting the business world (Risk, Marketing, Healthcare, Financial Services, etc.) Explains this new technology and how companies can use them effectively to gather the data that they need and glean critical insights Explores relevant topics such as data privacy, data visualization, unstructured data, crowd sourcing data scientists, cloud computing for big data, and much more.

Big Data Analytics Methods

Big Data Analytics Methods Book
Author : Peter Ghavami
Publisher : Walter de Gruyter GmbH & Co KG
Release : 2019-12-16
ISBN : 1547401567
Language : En, Es, Fr & De

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Book Description :

Big Data Analytics Methods unveils secrets to advanced analytics techniques ranging from machine learning, random forest classifiers, predictive modeling, cluster analysis, natural language processing (NLP), Kalman filtering and ensembles of models for optimal accuracy of analysis and prediction. More than 100 analytics techniques and methods provide big data professionals, business intelligence professionals and citizen data scientists insight on how to overcome challenges and avoid common pitfalls and traps in data analytics. The book offers solutions and tips on handling missing data, noisy and dirty data, error reduction and boosting signal to reduce noise. It discusses data visualization, prediction, optimization, artificial intelligence, regression analysis, the Cox hazard model and many analytics using case examples with applications in the healthcare, transportation, retail, telecommunication, consulting, manufacturing, energy and financial services industries. This book's state of the art treatment of advanced data analytics methods and important best practices will help readers succeed in data analytics.

Big Data Management

Big Data Management Book
Author : Peter Ghavami
Publisher : Walter de Gruyter GmbH & Co KG
Release : 2020-11-09
ISBN : 3110664062
Language : En, Es, Fr & De

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Book Description :

Data analytics is core to business and decision making. The rapid increase in data volume, velocity and variety offers both opportunities and challenges. While open source solutions to store big data, like Hadoop, offer platforms for exploring value and insight from big data, they were not originally developed with data security and governance in mind. Big Data Management discusses numerous policies, strategies and recipes for managing big data. It addresses data security, privacy, controls and life cycle management offering modern principles and open source architectures for successful governance of big data. The author has collected best practices from the world’s leading organizations that have successfully implemented big data platforms. The topics discussed cover the entire data management life cycle, data quality, data stewardship, regulatory considerations, data council, architectural and operational models are presented for successful management of big data. The book is a must-read for data scientists, data engineers and corporate leaders who are implementing big data platforms in their organizations.

Big Data Analytics with Spark and Hadoop

Big Data Analytics with Spark and Hadoop Book
Author : Venkat Ankam
Publisher : Unknown
Release : 2016-08-26
ISBN : 9781785884696
Language : En, Es, Fr & De

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Book Description :

A handy reference guide for data analysts and data scientists to fetch "Value" out of big data analytics using Spark on Hadoop ClustersAbout This Book* Practical tutorial with real-world examples that explores Spark on Hadoop clusters* This book is based on the latest version of Apache Spark and Hadoop integrated with the most commonly used tools* Learn about all the Spark stack components including the latest topics such as DataFrames, DataSets, and SparkRWho This Book Is ForThough this book is primarily aimed at data analysts and data scientists, it will also help architects, programmers, and practitioners. Knowledge of either Spark or Hadoop would be beneficial. It is assumed that you have basic programming background in Scala, Python, SQL, or R programming with basic Linux experience. Working experience within big data environments is not mandatory.What You Will Learn* Find out about and implement the tools and techniques of big data analytics using Spark on Hadoop clusters* Understand all the Hadoop and Spark ecosystem components and how Spark replaced MapReduce* Get to know all the Spark components: Spark Core, Spark SQL, DataFrames, DataSets, Streaming, MLLib, and Graphx* See batch and real-time data analytics using Spark Core, Spark SQL, and Spark Streaming* Get to grips with data science and machine learning using MLLib, H2O, Hivemall, Graphx, and SparkR* Get an introduction to all the new tools (based on Notebooks, Data Flow, and Spark as a Service) and their integrations with Spark and HadoopIn DetailThis book explains the fundamentals of Apache Spark and Hadoop, and how they are easily integrated together with the most commonly used tools and techniques. All the Spark components-Spark Core, Spark SQL, DataFrames, Data sets, Streaming, MLlib, Graphx, and Hadoop core components-HDFS, MapReduce, and Yarn are explored in greater depth with implementation examples on Spark and Hadoop clusters.The big data analytics industry is moving away from MapReduce to Spark. In this book, the advantages of Spark over MapReduce are explained at great depth so you can reap the benefits of in-memory speeds. The DataFrames API, Data Sources API, and new Data sets API are explained so you can build big data analytical applications.We'll explore real-time data analytics using Spark Streaming with Apache Kafka and HBase to help you build streaming applications. You'll get to know the machine learning techniques using MLLib and SparkR, and Graph Analytics with the GraphX component of Spark.You will also get the opportunity to start working with web-based notebooks such as Jupyter, Apache Zeppelin, and the data flow tool Apache NiFi to analyze and visualize data.

Big Data Analytics

Big Data Analytics Book
Author : Saumyadipta Pyne,B.L.S. Prakasa Rao,S.B. Rao
Publisher : Springer
Release : 2016-10-12
ISBN : 8132236289
Language : En, Es, Fr & De

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Book Description :

This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance; medicine and healthcare; genome, cytome and microbiome; graphs and networks; Internet of Things; Big Data standards; bench-marking of systems; and others. In addition to different applications, key algorithmic approaches such as graph partitioning, clustering and finite mixture modelling of high-dimensional data are also covered. The varied collection of themes in this volume introduces the reader to the richness of the emerging field of Big Data Analytics.

Big Data a Very Short Introduction

Big Data  a Very Short Introduction Book
Author : Dawn E. Holmes
Publisher : Oxford University Press
Release : 2017-10-23
ISBN : 0198779577
Language : En, Es, Fr & De

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Book Description :

Since long before computers were even thought of, data has been collected and organized by diverse cultures across the world. Once access to the Internet became a reality for large swathes of the world's population, the amount of data generated each day became huge, and continues to grow exponentially. It includes all our uploaded documents, video, and photos, all our social media traffic, our online shopping, even the GPS data from our cars. "Big Data" represents a qualitative change, not simply a quantitative one. The term refers both to the new technologies involved, and to the way it can be used by business and government. Dawn E. Holmes uses a variety of case studies to explain how data is stored, analyzed, and exploited by a variety of bodies from big companies to organizations concerned with disease control. Big data is transforming the way businesses operate, and the way medical research can be carried out. At the same time, it raises important ethical issues; Holmes discusses cases such as the Snowden affair, data security, and domestic smart devices which can be hijacked by hackers. ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable.

High Performance Big Data Analytics

High Performance Big Data Analytics Book
Author : Pethuru Raj,Anupama Raman,Dhivya Nagaraj,Siddhartha Duggirala
Publisher : Springer
Release : 2015-10-16
ISBN : 331920744X
Language : En, Es, Fr & De

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Book Description :

This book presents a detailed review of high-performance computing infrastructures for next-generation big data and fast data analytics. Features: includes case studies and learning activities throughout the book and self-study exercises in every chapter; presents detailed case studies on social media analytics for intelligent businesses and on big data analytics (BDA) in the healthcare sector; describes the network infrastructure requirements for effective transfer of big data, and the storage infrastructure requirements of applications which generate big data; examines real-time analytics solutions; introduces in-database processing and in-memory analytics techniques for data mining; discusses the use of mainframes for handling real-time big data and the latest types of data management systems for BDA; provides information on the use of cluster, grid and cloud computing systems for BDA; reviews the peer-to-peer techniques and tools and the common information visualization techniques, used in BDA.

Practical Big Data Analytics

Practical Big Data Analytics Book
Author : Nataraj Dasgupta
Publisher : Packt Publishing Ltd
Release : 2018-01-15
ISBN : 1783554401
Language : En, Es, Fr & De

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Book Description :

Get command of your organizational Big Data using the power of data science and analytics Key Features A perfect companion to boost your Big Data storing, processing, analyzing skills to help you take informed business decisions Work with the best tools such as Apache Hadoop, R, Python, and Spark for NoSQL platforms to perform massive online analyses Get expert tips on statistical inference, machine learning, mathematical modeling, and data visualization for Big Data Book Description Big Data analytics relates to the strategies used by organizations to collect, organize and analyze large amounts of data to uncover valuable business insights that otherwise cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization's data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages and BI Tools, selecting the right combination of technologies is an even greater challenge. This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology with the practical ground reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB and even learn how to write R code for neural networks. By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using different tools and methods articulated in this book. What you will learn - Get a 360-degree view into the world of Big Data, data science and machine learning - Broad range of technical and business Big Data analytics topics that caters to the interests of the technical experts as well as corporate IT executives - Get hands-on experience with industry-standard Big Data and machine learning tools such as Hadoop, Spark, MongoDB, KDB+ and R - Create production-grade machine learning BI Dashboards using R and R Shiny with step-by-step instructions - Learn how to combine open-source Big Data, machine learning and BI Tools to create low-cost business analytics applications - Understand corporate strategies for successful Big Data and data science projects - Go beyond general-purpose analytics to develop cutting-edge Big Data applications using emerging technologies Who this book is for The book is intended for existing and aspiring Big Data professionals who wish to become the go-to person in their organization when it comes to Big Data architecture, analytics, and governance. While no prior knowledge of Big Data or related technologies is assumed, it will be helpful to have some programming experience.

Deep Learning Techniques and Optimization Strategies in Big Data Analytics

Deep Learning Techniques and Optimization Strategies in Big Data Analytics Book
Author : Thomas, J. Joshua,Karagoz, Pinar,Ahamed, B. Bazeer,Vasant, Pandian
Publisher : IGI Global
Release : 2019-11-29
ISBN : 1799811948
Language : En, Es, Fr & De

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Book Description :

Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there’s a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.

Big Data Analytics

Big Data Analytics Book
Author : Frank Millstein
Publisher : Frank Millstein
Release : 2020-08-14
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Big Data Analytics - 2 BOOK BUNDLE!! Data Analytics With Python Data is the foundation of this digital age that we live in. With this book, you are going to learn how to organize and analyze data and how to interpret vast sources of information. This book covers various topics on data analytics such as data analytics applications, data analytics process, using Python for data analytics, Python libraries for data analytics and many other that will help you kick-start your data analytics journey from the very beginning. In this book you are going to learn how to use Python its tools in order to interpret data and examine those interesting data trends and information, which are important in predicting the future. Whether you are dealing with some medical data, sales data, web page data, you can use Python in order to interpret data, analyze it and obtain this valuable information. You can also use this data for creating data analytics models and predictions. Here Is A Brief Preview of What You’ll Learn In This Book… Data analytics applications Data analytics process How to install and run Python Python data structures and Python libraries Python conditional construct and iteration Data exploration using Pandas Pandas series and dataframes Data munging and distribution analysis Carrying out binary operations Data manipulation and categorical variable analysis How to build a predictive model And of course much, much more! Natural Language Processing With Python This book is a perfect beginner's guide to natural language processing. It is offering an easy to understand guide to implementing NLP techniques using Python. Natural language processing has been around for more than fifty years, but just recently with greater amounts of data present and better computational powers, it has gained a greater popularity. Given the importance of data, there is no wonder why natural language processing is on the rise. If you are interested in learning more, this book will serve as your best companion on this journey introducing you to this challenging, yet extremely engaging world of automatic manipulation of our human language. It covers all the basics you need to know before you dive deeper into NLP and solving more complex NLP tasks in Python. Here Is a Preview of What You’ll Learn Here… The main challenges of natural language processing The history of natural language processing How natural langauge processing actually works The main natural language processing applications Text preprocessing and noise removal Feature engineering and syntactic parsing Part of speech tagging and named entity extraction Topic modeling and word embedding Text classification problems Working with text data using NLTK Text summarization and sentiment analysis And much, much more... Get this book bundle NOW and SAVE money!

Big Data Analytics A Management Perspective

Big Data Analytics  A Management Perspective Book
Author : Francesco Corea
Publisher : Springer
Release : 2016-05-24
ISBN : 3319389920
Language : En, Es, Fr & De

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Book Description :

This book is about innovation, big data, and data science seen from a business perspective. Big data is a buzzword nowadays, and there is a growing necessity within practitioners to understand better the phenomenon, starting from a clear stated definition. This book aims to be a starting reading for executives who want (and need) to keep the pace with the technological breakthrough introduced by new analytical techniques and piles of data. Common myths about big data will be explained, and a series of different strategic approaches will be provided. By browsing the book, it will be possible to learn how to implement a big data strategy and how to use a maturity framework to monitor the progress of the data science team, as well as how to move forward from one stage to the next. Crucial challenges related to big data will be discussed, where some of them are more general - such as ethics, privacy, and ownership – while others concern more specific business situations (e.g., initial public offering, growth strategies, etc.). The important matter of selecting the right skills and people for an effective team will be extensively explained, and practical ways to recognize them and understanding their personalities will be provided. Finally, few relevant technological future trends will be acknowledged (i.e., IoT, Artificial intelligence, blockchain, etc.), especially for their close relation with the increasing amount of data and our ability to analyse them faster and more effectively.

Cognitive Computing and Big Data Analytics

Cognitive Computing and Big Data Analytics Book
Author : Judith S. Hurwitz,Marcia Kaufman,Adrian Bowles
Publisher : John Wiley & Sons
Release : 2015-04-08
ISBN : 1118896785
Language : En, Es, Fr & De

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Book Description :

A comprehensive guide to learning technologies that unlock thevalue in big data Cognitive Computing provides detailed guidance towardbuilding a new class of systems that learn from experience andderive insights to unlock the value of big data. This book helpstechnologists understand cognitive computing's underlyingtechnologies, from knowledge representation techniques and naturallanguage processing algorithms to dynamic learning approaches basedon accumulated evidence, rather than reprogramming. Detailed caseexamples from the financial, healthcare, and manufacturing walkreaders step-by-step through the design and testing of cognitivesystems, and expert perspectives from organizations such asCleveland Clinic, Memorial Sloan-Kettering, as well as commercialvendors that are creating solutions. These organizations provideinsight into the real-world implementation of cognitive computingsystems. The IBM Watson cognitive computing platform is describedin a detailed chapter because of its significance in helping todefine this emerging market. In addition, the book includesimplementations of emerging projects from Qualcomm, Hitachi, Googleand Amazon. Today's cognitive computing solutions build on establishedconcepts from artificial intelligence, natural language processing,ontologies, and leverage advances in big data management andanalytics. They foreshadow an intelligent infrastructure thatenables a new generation of customer and context-aware smartapplications in all industries. Cognitive Computing is a comprehensive guide to thesubject, providing both the theoretical and practical guidancetechnologists need. Discover how cognitive computing evolved from promise toreality Learn the elements that make up a cognitive computingsystem Understand the groundbreaking hardware and softwaretechnologies behind cognitive computing Learn to evaluate your own application portfolio to find thebest candidates for pilot projects Leverage cognitive computing capabilities to transform theorganization Cognitive systems are rightly being hailed as the new era ofcomputing. Learn how these technologies enable emerging firms tocompete with entrenched giants, and forward-thinking establishedfirms to disrupt their industries. Professionals who currently workwith big data and analytics will see how cognitive computing buildson their foundation, and creates new opportunities. CognitiveComputing provides complete guidance to this new level ofhuman-machine interaction.

Data Science and Big Data Analytics in Smart Environments

Data Science and Big Data Analytics in Smart Environments Book
Author : Taylor & Francis Group
Publisher : CRC Press
Release : 2021-05-15
ISBN : 9780367407131
Language : En, Es, Fr & De

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Book Description :

Most applications generate large datasets, like social networking and social influence programs, smart cities applications, smart house environments, Cloud applications, public web sites, scientific experiments and simulations, data warehouse, monitoring platforms, and e-government services. Data grows rapidly, since applications produce continuously increasing volumes of both unstructured and structured data. Large-scale interconnected systems aim to aggregate and efficiently exploit the power of widely distributed resources. In this context, major solutions for scalability, mobility, reliability, fault tolerance and security are required to achieve high performance and to create a smart environment. The impact on data processing, transfer and storage is the need to re-evaluate the approaches and solutions to better answer the user needs. A variety of solutions for specific applications and platforms exist so a thorough and systematic analysis of existing solutions for data science, data analytics, methods and algorithms used in Big Data processing and storage environments is significant in designing and implementing a smart environment. Fundamental issues pertaining to smart environments (smart cities, ambient assisted leaving, smart houses, green houses, cyber physical systems, etc.) are reviewed. Most of the current efforts still do not adequately address the heterogeneity of different distributed systems, the interoperability between them, and the systems resilience. This book will primarily encompass practical approaches that promote research in all aspects of data processing, data analytics, data processing in different type of systems: Cluster Computing, Grid Computing, Peer-to-Peer, Cloud/Edge/Fog Computing, all involving elements of heterogeneity, having a large variety of tools and software to manage them. The main role of resource management techniques in this domain is to create the suitable frameworks for development of applications and deployment in smart environments, with respect to high performance. The book focuses on topics covering algorithms, architectures, management models, high performance computing techniques and large-scale distributed systems.

The Internet of Things and Big Data Analytics

The Internet of Things and Big Data Analytics Book
Author : Pethuru Raj,T. Poongodi,Manju Khari,Balamurugan Balusamy
Publisher : Auerbach Publications
Release : 2020
ISBN : 9780367342890
Language : En, Es, Fr & De

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Book Description :

"This book is presents academic and practical research in IoT and big data. With contributions from both practitioners and academic researchers, the book examines new technology and compares it to existing technology. Experimental case studies are related to real-time scenarios"--

Internet of Things and Big Data Analytics Toward Next Generation Intelligence

Internet of Things and Big Data Analytics Toward Next Generation Intelligence Book
Author : Nilanjan Dey,Aboul Ella Hassanien,Chintan Bhatt,Amira S. Ashour,Suresh Chandra Satapathy
Publisher : Springer
Release : 2017-08-14
ISBN : 331960435X
Language : En, Es, Fr & De

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Book Description :

This book highlights state-of-the-art research on big data and the Internet of Things (IoT), along with related areas to ensure efficient and Internet-compatible IoT systems. It not only discusses big data security and privacy challenges, but also energy-efficient approaches to improving virtual machine placement in cloud computing environments. Big data and the Internet of Things (IoT) are ultimately two sides of the same coin, yet extracting, analyzing and managing IoT data poses a serious challenge. Accordingly, proper analytics infrastructures/platforms should be used to analyze IoT data. Information technology (IT) allows people to upload, retrieve, store and collect information, which ultimately forms big data. The use of big data analytics has grown tremendously in just the past few years. At the same time, the IoT has entered the public consciousness, sparking people’s imaginations as to what a fully connected world can offer. Further, the book discusses the analysis of real-time big data to derive actionable intelligence in enterprise applications in several domains, such as in industry and agriculture. It explores possible automated solutions in daily life, including structures for smart cities and automated home systems based on IoT technology, as well as health care systems that manage large amounts of data (big data) to improve clinical decisions. The book addresses the security and privacy of the IoT and big data technologies, while also revealing the impact of IoT technologies on several scenarios in smart cities design. Intended as a comprehensive introduction, it offers in-depth analysis and provides scientists, engineers and professionals the latest techniques, frameworks and strategies used in IoT and big data technologies.

Big Data Analytics

Big Data Analytics Book
Author : Ladjel Bellatreche
Publisher : Springer Nature
Release : 2021-04-13
ISBN : 3030666654
Language : En, Es, Fr & De

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Book Description :

Download Big Data Analytics book written by Ladjel Bellatreche, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.