LEADER 04488nam 2200661 450 001 9910811945103321 005 20230202102651.0 010 $a1-78646-372-5 035 $a(CKB)3710000000777467 035 $a(Au-PeEL)EBL4620799 035 $a(CaPaEBR)ebr11350750 035 $a(CaONFJC)MIL944176 035 $a(OCoLC)955130608 035 $a(CaSebORM)9781786466457 035 $a(MiAaPQ)EBC4620799 035 $a(PPN)220200939 035 $a(EXLCZ)993710000000777467 100 $a20170307d2016 uy| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aBig data analytics with R $eutilize R to uncover hidden patterns in your big data /$fSimon Walkowiak 205 $a1st edition 210 1$aBirmingham :$cPackt Publishing,$d2016. 215 $a1 online resource (498 pages) $cillustrations 225 1 $aCommunity experience distilled 300 $aIncludes index. 311 0 $a1-78646-645-7 330 $aUtilize R to uncover hidden patterns in your Big Data About This Book Perform computational analyses on Big Data to generate meaningful results Get a practical knowledge of R programming language while working on Big Data platforms like Hadoop, Spark, H2O and SQL/NoSQL databases, Explore fast, streaming, and scalable data analysis with the most cutting-edge technologies in the market Who This Book Is For This book is intended for Data Analysts, Scientists, Data Engineers, Statisticians, Researchers, who want to integrate R with their current or future Big Data workflows. It is assumed that readers have some experience in data analysis and understanding of data management and algorithmic processing of large quantities of data, however they may lack specific skills related to R. What You Will Learn Learn about current state of Big Data processing using R programming language and its powerful statistical capabilities 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 on a multi-node Hadoop cluster, e.g. electricity consumption across various socio-demographic indicators and bike share scheme usage Explore the compatibility of R with Hadoop, Spark, SQL and NoSQL databases, and H2O platform In Detail Big Data analytics is the process of examining large and complex data sets that often exceed the computational capabilities. R is a leading programming language of data science, consisting of powerful functions to tackle all problems related to Big Data processing. The book will begin with a brief introduction to the Big Data world and its current industry standards. With introduction to the R language and presenting its development, structure, applications in real world, and its shortcomings. Book will progress towards revision of major R functions for data management and transformations. Readers will be introduce to Cloud based Big Data solutions (e.g. Amazon EC2 instances and Amazon RDS, Microsoft Azure and its HDInsight clusters) and also provide guidance on R connectivity with relational and non-relational databases such as MongoDB and HBase etc. It will further expand to include Big Data tools such as Apache Hadoop ecosystem, HDFS and MapReduce frameworks. Also other R compatible tools such as Apache Spark, its machine learning library Spark MLlib, as well as H2O. Style and approach This book will serve as a practical guide... 410 0$aCommunity experience distilled. 606 $aR (Computer program language) 606 $aData mining 606 $aInformation visualization 606 $atext and data mining$9eng$2EUROVOC 606 $aprogramming language$9eng$2EUROVOC 606 $abig data$9eng$2EUROVOC 606 $acloud computing$9eng$2EUROVOC 606 $adata processing$9eng$2EUROVOC 606 $asoftware$9eng$2EUROVOC 615 0$aR (Computer program language) 615 0$aData mining. 615 0$aInformation visualization. 615 7$atext and data mining. 615 7$aprogramming language. 615 7$abig data. 615 7$acloud computing. 615 7$adata processing. 615 7$asoftware. 700 $aWalkowiak$b Simon$01659750 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910811945103321 996 $aBig data analytics with R$94014555 997 $aUNINA