Data Analytics And Big Data

Data Analytics and Big Data PDF
Author: Soraya Sedkaoui
Publisher: John Wiley & Sons
ISBN: 1786303264
Size: 63.37 MB
Format: PDF, Mobi
Category : Computers
Languages : en
Pages : 220
View: 900
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Data Analytics And Big Data

by Soraya Sedkaoui, Data Analytics And Big Data Books available in PDF, EPUB, Mobi Format. Download Data Analytics And Big Data books, The main purpose of this book is to investigate, explore and describe approaches and methods to facilitate data understanding through analytics solutions based on its principles, concepts and applications. But analyzing data is also about involving the use of software. For this, and in order to cover some aspect of data analytics, this book uses software (Excel, SPSS, Python, etc) which can help readers to better understand the analytics process in simple terms and supporting useful methods in its application.




Big Data Analytics

Big Data Analytics PDF
Author: Anirban Mondal
Publisher: Springer
ISBN: 3030047806
Size: 17.74 MB
Format: PDF, Kindle
Category : Computers
Languages : en
Pages : 424
View: 4771
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Big Data Analytics

by Anirban Mondal, Big Data Analytics Books available in PDF, EPUB, Mobi Format. Download Big Data Analytics books, This book constitutes the refereed proceedings of the 6th International Conference on Big Data analytics, BDA 2018, held in Warangal, India, in December 2018. The 29 papers presented in this volume were carefully reviewed and selected from 93 submissions. The papers are organized in topical sections named: big data analytics: vision and perspectives; financial data analytics and data streams; web and social media data; big data systems and frameworks; predictive analytics in healthcare and agricultural domains; and machine learning and pattern mining.




Data Science And Big Data Analytics In Smart Environments

Data Science and Big Data Analytics in Smart Environments PDF
Author: Taylor & Francis Group
Publisher: CRC Press
ISBN: 9780367407131
Size: 34.60 MB
Format: PDF, ePub, Docs
Category :
Languages : en
Pages : 275
View: 2273
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Data Science And Big Data Analytics In Smart Environments

by Taylor & Francis Group, Data Science And Big Data Analytics In Smart Environments Books available in PDF, EPUB, Mobi Format. Download Data Science And Big Data Analytics In Smart Environments books, 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.




Data Science And Big Data Analytics

Data Science and Big Data Analytics PDF
Author: Durgesh Kumar Mishra
Publisher: Springer
ISBN: 9811076413
Size: 51.85 MB
Format: PDF, ePub
Category : Computers
Languages : en
Pages : 406
View: 2777
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Data Science And Big Data Analytics

by Durgesh Kumar Mishra, Data Science And Big Data Analytics Books available in PDF, EPUB, Mobi Format. Download Data Science And Big Data Analytics books, This book presents conjectural advances in big data analysis, machine learning and computational intelligence, as well as their potential applications in scientific computing. It discusses major issues pertaining to big data analysis using computational intelligence techniques, and the conjectural elements are supported by simulation and modelling applications to help address real-world problems. An extensive bibliography is provided at the end of each chapter. Further, the main content is supplemented by a wealth of figures, graphs, and tables, offering a valuable guide for researchers in the field of big data analytics and computational intelligence.




Data Science And Big Data Analytics

Data Science and Big Data Analytics PDF
Author: EMC Education Services
Publisher: John Wiley & Sons
ISBN: 1118876059
Size: 42.73 MB
Format: PDF, Mobi
Category : Computers
Languages : en
Pages : 432
View: 572
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Data Science And Big Data Analytics

by EMC Education Services, Data Science And Big Data Analytics Books available in PDF, EPUB, Mobi Format. Download Data Science And Big Data Analytics books, Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Corresponding data sets are available from the book’s page at Wiley which you can find on the Wiley site by searching for the ISBN 9781118876138. Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!




Machine Learning And Big Data Analytics Paradigms Analysis Applications And Challenges

Machine Learning and Big Data Analytics Paradigms  Analysis  Applications and Challenges PDF
Author: Aboul Ella Hassanien
Publisher: Springer Nature
ISBN: 303059338X
Size: 39.95 MB
Format: PDF
Category : Computers
Languages : en
Pages : 648
View: 5570
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Machine Learning And Big Data Analytics Paradigms Analysis Applications And Challenges

by Aboul Ella Hassanien, Machine Learning And Big Data Analytics Paradigms Analysis Applications And Challenges Books available in PDF, EPUB, Mobi Format. Download Machine Learning And Big Data Analytics Paradigms Analysis Applications And Challenges books, This book is intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data analytics and its applications.




Big Data Analytics With Hadoop 3

Big Data Analytics with Hadoop 3 PDF
Author: Sridhar Alla
Publisher: Packt Publishing Ltd
ISBN: 1788624955
Size: 39.34 MB
Format: PDF, Mobi
Category : Computers
Languages : en
Pages : 482
View: 3721
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Big Data Analytics With Hadoop 3

by Sridhar Alla, Big Data Analytics With Hadoop 3 Books available in PDF, EPUB, Mobi Format. Download Big Data Analytics With Hadoop 3 books, Explore big data concepts, platforms, analytics, and their applications using the power of Hadoop 3 Key Features Learn Hadoop 3 to build effective big data analytics solutions on-premise and on cloud Integrate Hadoop with other big data tools such as R, Python, Apache Spark, and Apache Flink Exploit big data using Hadoop 3 with real-world examples Book Description Apache Hadoop is the most popular platform for big data processing, and can be combined with a host of other big data tools to build powerful analytics solutions. Big Data Analytics with Hadoop 3 shows you how to do just that, by providing insights into the software as well as its benefits with the help of practical examples. Once you have taken a tour of Hadoop 3’s latest features, you will get an overview of HDFS, MapReduce, and YARN, and how they enable faster, more efficient big data processing. You will then move on to learning how to integrate Hadoop with the open source tools, such as Python and R, to analyze and visualize data and perform statistical computing on big data. As you get acquainted with all this, you will explore how to use Hadoop 3 with Apache Spark and Apache Flink for real-time data analytics and stream processing. In addition to this, you will understand how to use Hadoop to build analytics solutions on the cloud and an end-to-end pipeline to perform big data analysis using practical use cases. By the end of this book, you will be well-versed with the analytical capabilities of the Hadoop ecosystem. You will be able to build powerful solutions to perform big data analytics and get insight effortlessly. What you will learn Explore the new features of Hadoop 3 along with HDFS, YARN, and MapReduce Get well-versed with the analytical capabilities of Hadoop ecosystem using practical examples Integrate Hadoop with R and Python for more efficient big data processing Learn to use Hadoop with Apache Spark and Apache Flink for real-time data analytics Set up a Hadoop cluster on AWS cloud Perform big data analytics on AWS using Elastic Map Reduce Who this book is for Big Data Analytics with Hadoop 3 is for you if you are looking to build high-performance analytics solutions for your enterprise or business using Hadoop 3’s powerful features, or you’re new to big data analytics. A basic understanding of the Java programming language is required.




Big Data Science Analytics

Big Data Science   Analytics PDF
Author: Arshdeep Bahga
Publisher: Vpt
ISBN: 9780996025539
Size: 35.81 MB
Format: PDF
Category :
Languages : en
Pages : 544
View: 3501
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Big Data Science Analytics

by Arshdeep Bahga, Big Data Science Analytics Books available in PDF, EPUB, Mobi Format. Download Big Data Science Analytics books, We are living in the dawn of what has been termed as the "Fourth Industrial Revolution," which is marked through the emergence of "cyber-physical systems" where software interfaces seamlessly over networks with physical systems, such as sensors, smartphones, vehicles, power grids or buildings, to create a new world of Internet of Things (IoT). Data and information are fuel of this new age where powerful analytics algorithms burn this fuel to generate decisions that are expected to create a smarter and more efficient world for all of us to live in. This new area of technology has been defined as Big Data Science and Analytics, and the industrial and academic communities are realizing this as a competitive technology that can generate significant new wealth and opportunity. Big data is defined as collections of datasets whose volume, velocity or variety is so large that it is difficult to store, manage, process and analyze the data using traditional databases and data processing tools. Big data science and analytics deals with collection, storage, processing and analysis of massive-scale data. Industry surveys, by Gartner and e-Skills, for instance, predict that there will be over 2 million job openings for engineers and scientists trained in the area of data science and analytics alone, and that the job market is in this area is growing at a 150 percent year-over-year growth rate. We have written this textbook, as part of our expanding "A Hands-On Approach"(TM) series, to meet this need at colleges and universities, and also for big data service providers who may be interested in offering a broader perspective of this emerging field to accompany their customer and developer training programs. The typical reader is expected to have completed a couple of courses in programming using traditional high-level languages at the college-level, and is either a senior or a beginning graduate student in one of the science, technology, engineering or mathematics (STEM) fields. An accompanying website for this book contains additional support for instruction and learning (www.big-data-analytics-book.com) The book is organized into three main parts, comprising a total of twelve chapters. Part I provides an introduction to big data, applications of big data, and big data science and analytics patterns and architectures. A novel data science and analytics application system design methodology is proposed and its realization through use of open-source big data frameworks is described. This methodology describes big data analytics applications as realization of the proposed Alpha, Beta, Gamma and Delta models, that comprise tools and frameworks for collecting and ingesting data from various sources into the big data analytics infrastructure, distributed filesystems and non-relational (NoSQL) databases for data storage, and processing frameworks for batch and real-time analytics. This new methodology forms the pedagogical foundation of this book. Part II introduces the reader to various tools and frameworks for big data analytics, and the architectural and programming aspects of these frameworks, with examples in Python. We describe Publish-Subscribe messaging frameworks (Kafka & Kinesis), Source-Sink connectors (Flume), Database Connectors (Sqoop), Messaging Queues (RabbitMQ, ZeroMQ, RestMQ, Amazon SQS) and custom REST, WebSocket and MQTT-based connectors. The reader is introduced to data storage, batch and real-time analysis, and interactive querying frameworks including HDFS, Hadoop, MapReduce, YARN, Pig, Oozie, Spark, Solr, HBase, Storm, Spark Streaming, Spark SQL, Hive, Amazon Redshift and Google BigQuery. Also described are serving databases (MySQL, Amazon DynamoDB, Cassandra, MongoDB) and the Django Python web framework. Part III introduces the reader to various machine learning algorithms with examples using the Spark MLlib and H2O frameworks, and visualizations using frameworks such as Lightning, Pygal and Seaborn.




Handbook Of Big Data Analytics

Handbook of Big Data Analytics PDF
Author: Wolfgang Karl Härdle
Publisher: Springer
ISBN: 3319182846
Size: 15.36 MB
Format: PDF, Docs
Category : Computers
Languages : en
Pages : 538
View: 4797
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Handbook Of Big Data Analytics

by Wolfgang Karl Härdle, Handbook Of Big Data Analytics Books available in PDF, EPUB, Mobi Format. Download Handbook Of Big Data Analytics books, Addressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field. To do so, it covers statistical methods for high-dimensional problems, algorithmic designs, computation tools, analysis flows and the software-hardware co-designs that are needed to support insightful discoveries from big data. The book is primarily intended for statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics. Readers should have a solid background in statistics and computer science.




Big Data Analytics

BIG DATA ANALYTICS PDF
Author: Raj Kamal
Publisher: McGraw-Hill Education
ISBN: 9353164974
Size: 22.66 MB
Format: PDF, Kindle
Category : Computers
Languages : en
Pages : 534
View: 2390
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Big Data Analytics

by Raj Kamal, Big Data Analytics Books available in PDF, EPUB, Mobi Format. Download Big Data Analytics books, 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.