Big Data Analytics with R by Simon Walkowiak
A practical guide to large-scale data analysis with R About This Book* Perform exploratory data analyses at scale and generate meaningful results* Work with multiple techniques to uncover hidden patterns in your data* get a practical coverage of R while working with Spark, Hadoop, Storm, and moreWho This Book Is For This book is for Statisticians, Analysts and upcoming Data Scientists. It is also assumed that readers will have some previous experience in data analysis and understanding of data management and algorithmic processing of large quantities of data, however they may lack R skills related to specific Big Data tools compatible with R programming language. What You Will Learn* The current state of Big Data processing using R programming language and its powerful statistical capabilities* Easily deploy Big Data analytics platforms with selected Big Data tools supported by R in a cost-effective and time-saving manner* Apply the R language to real-world Big Data problems e.g. electricity consumption across various socio-demographic indicators, near real-time Twitter sentiment analysis for specific keywords etc.* Explore the compatibility of R with Spark, Docker and StormIn Detail Big data analytics is the process of examining large data sets that contain a variety of data types. The R programming language is one of the leading languages of data science; it boasts powerful and popular packages to tackle nearly all the problems in big data. The book will begin with a brief introduction to the Big Data world and current industry standards in Big Data analysis. It will progress to a gentle introduction to the R language by presenting its development, language structure, applications in research and business, and its traditional shortcomings. The book will further provide readers with a revision of major R functions for data management and transformations and will eventually present a number of third-party packages allowing High Performance Computing with R. The book will then introduce Cloud based Big Data solutions (Amazon EC2, Windows Azure & HDInsight, Google Cloud Platform etc.) and also provide guidance on R connectivity with relational (SQL-based e.g. MySQL) and non-relational (NoSQL) databases such as Cassandra, MongoDB etc. It will further expand to include industry standard Big Data tools such as Apache Hadoop ecosystem (with HBase etc.) and will thoroughly explain its HDFS and MapReduce frameworks. The next few chapters will address other Big Data tools and most recent third-party packages allowing compatibility of R with Spark, Docker and Storm for fast and streaming data processing; visualization techniques using ggplot, shiny and rCharts.
Read online Big Data Analytics with R Buy and read online Big Data Analytics with R Download Big Data Analytics with R ebook, pdf, djvu, epub, mobi, fb2, zip, rar, torrent Download to iPad/iPhone/iOS, B&N nook Big Data Analytics with R ebook, pdf, djvu, epub, mobi, fb2, zip, rar, torrent
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Author: Simon Walkowiak
Page Count: 323 pages
Published Date: 29 Jul 2016
Publisher: Packt Publishing Limited
Publication Country: Birmingham, United Kingdom
Language: none
ISBN: 9781786466457
Download Link: Big Data Analytics with R
---------------------------------------------------------------
Author: Simon Walkowiak
Page Count: 323 pages
Published Date: 29 Jul 2016
Publisher: Packt Publishing Limited
Publication Country: Birmingham, United Kingdom
Language: none
ISBN: 9781786466457
Download Link: Big Data Analytics with R
---------------------------------------------------------------
A practical guide to large-scale data analysis with R About This Book* Perform exploratory data analyses at scale and generate meaningful results* Work with multiple techniques to uncover hidden patterns in your data* get a practical coverage of R while working with Spark, Hadoop, Storm, and moreWho This Book Is For This book is for Statisticians, Analysts and upcoming Data Scientists. It is also assumed that readers will have some previous experience in data analysis and understanding of data management and algorithmic processing of large quantities of data, however they may lack R skills related to specific Big Data tools compatible with R programming language. What You Will Learn* The current state of Big Data processing using R programming language and its powerful statistical capabilities* Easily deploy Big Data analytics platforms with selected Big Data tools supported by R in a cost-effective and time-saving manner* Apply the R language to real-world Big Data problems e.g. electricity consumption across various socio-demographic indicators, near real-time Twitter sentiment analysis for specific keywords etc.* Explore the compatibility of R with Spark, Docker and StormIn Detail Big data analytics is the process of examining large data sets that contain a variety of data types. The R programming language is one of the leading languages of data science; it boasts powerful and popular packages to tackle nearly all the problems in big data. The book will begin with a brief introduction to the Big Data world and current industry standards in Big Data analysis. It will progress to a gentle introduction to the R language by presenting its development, language structure, applications in research and business, and its traditional shortcomings. The book will further provide readers with a revision of major R functions for data management and transformations and will eventually present a number of third-party packages allowing High Performance Computing with R. The book will then introduce Cloud based Big Data solutions (Amazon EC2, Windows Azure & HDInsight, Google Cloud Platform etc.) and also provide guidance on R connectivity with relational (SQL-based e.g. MySQL) and non-relational (NoSQL) databases such as Cassandra, MongoDB etc. It will further expand to include industry standard Big Data tools such as Apache Hadoop ecosystem (with HBase etc.) and will thoroughly explain its HDFS and MapReduce frameworks. The next few chapters will address other Big Data tools and most recent third-party packages allowing compatibility of R with Spark, Docker and Storm for fast and streaming data processing; visualization techniques using ggplot, shiny and rCharts.
Read online Big Data Analytics with R Buy and read online Big Data Analytics with R Download Big Data Analytics with R ebook, pdf, djvu, epub, mobi, fb2, zip, rar, torrent Download to iPad/iPhone/iOS, B&N nook Big Data Analytics with R ebook, pdf, djvu, epub, mobi, fb2, zip, rar, torrent