Data Analytics Using R

R is a GNU open Source Tool, with S-language pedigree, skilled in statistical computing and statistical charting. An open source project launched by Revolution Analytics Rhadoop the R language with Hadoop, which is a good place to play R language expertise. The vast number of R language enthusiasts with powerful tools Rhadoop, can be in the field of large data, which is undoubtedly a good news for R language programmers. The author gave a detailed explanation of R language and Hadoop from a programmer's point of view. The following is the original: Preface wrote several ...

With large data being adopted by more enterprises, the compilation and production language of data processing and analysis algorithms have been widely concerned. and unknowingly, open source statistics language R has become a basic technology for large data scientists and developers. 　　In all programming languages and techniques, popularity has soared. The following is the translation through the integration with the large data processing tools, R provides the depth statistical capability of large datasets, including statistical analysis and data-driven visualization. In industries such as finance, pharmaceuticals, media, and sales, which can directly take decisions from data, R has been applied in depth. ...

R as a source of data statistical analysis language is imperceptibly in the enterprise to expand their influence.   Unique extensions provide free extensions and allow the R language engine to run on the Hadoop cluster. R language is mainly used for statistical analysis, drawing language and operating environment. R was originally developed by Ross Ihaka and Robert Gentleman from Oakland University in New Zealand. (also known as R) is now being developed by the R Development core team. R is a GNU project based on the S language, so you can also ...

Introduction: It is well known that R is unparalleled in solving statistical problems. But R is slow at data speeds up to 2G, creating a solution that runs distributed algorithms in conjunction with Hadoop, but is there a team that uses solutions like python + Hadoop? R Such origins in the statistical computer package and Hadoop combination will not be a problem? The answer from the king of Frank: Because they do not understand the characteristics of R and Hadoop application scenarios, just ...

The explosive growth of data has put pressure on companies at the same time, the development of data-driven business philosophy, enterprises and other organizations have to pay attention to the role of data statistics and analysis, for statistical computing and graphical and born of the R language to cater to this huge demand, in order to help enterprises better grasp and use of R language, 　　Responding to the need for statistical programming in the big Data Age, Revolution Analytics launched a new toolkit to support R language. David Smith is Revolution Analytics's community director and new Open ...

Having just announced the easing of computing and memory limitations, Teradata promptly announced the acquisition of R-language analytics capabilities from Aster and announced the acquisition of Revelytix and Hadapt by Teradata Labs. The former focuses primarily on data management on Hadoop, while Hadapt is a focused SQL-on-Hadoop company. Clearly, Teradata is accelerating its efforts to build a unified data architecture. Construct a unified data structure In fact, structured data and unstructured data through traditional SQL analysis and ...

R: It's not a real language. Part of the reason we learn about R is that it's not really a programming language. John Cook, an R expert, said: "R is a statistical interactive environment, not a real programming language." It is more helpful to think of R as an interactive environment containing programming languages. "But as Bob Muenchen emphasizes, R is even harder for people who are proficient in SAS and SPSS data tools." About R for analyst ...

Now, "Big data" has become one of the hottest words, more and more enterprises began to pay attention to and embrace large data, 2014 Big data will have more substantial progress, in which Hadoop and R language will be the protagonist. "Big Data" has become one of the most frequently used technical hot words in the 2013. The corresponding market has also seen rapid growth in the year. Hadoop and its ecosystems, which are associated with large data, have become a common tool for data scientists from technologies that were previously used by very talented programmers and engineers. More and more enterprises begin to embrace ...

Now, "Big data" has become one of the hottest words, more and more enterprises began to pay attention to and embrace large data, 2014 Big data will have more substantial progress, in which Hadoop and R language will be the protagonist. "Big Data" has become one of the most frequently used technical hot words in the 2013. The corresponding market has also seen rapid growth in the year. Hadoop and its ecosystems, which are associated with large data, have become a common tool for data scientists from technologies that were previously used by very talented programmers and engineers. More and more enterprises begin to embrace ...

At the moment, "big data" has become one of the hottest technical terms of the 2013, and in the past year, the growth and change of the market is not insignificant. At the same time, we have seen a change in the use of Hadoop and its ecosystem from top technical talent to data scientists. More and more enterprises embrace large data technology and apply it to production environment. So what will happen to the trend of big data in the 2014, and here's a look at 12 predictions from CIOs: 1. People stop talking about big data for 2014, and big data stops saying ...