R Big Data Packages

Which of the following 5 languages are NODE, LUA, Python, Ruby, R, and which will be better applied in the 2014? I don't hesitate to choose R. 　　R is not only 2014, but also the protagonist for a longer period of time. 1. My programming background programmer, Architect, from the beginning of programming to today, has been convinced that Java is the language to change the world, Java has done, and has been very brilliant. But when the world of Java is becoming bigger and larger, when it becomes omnipotent, it is not professional enough for other languages to develop ...

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. ...

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 ...

With the upsurge of large data, there are flood-like information in almost every field, and it is far from satisfying to do data processing in the face of thousands of users ' browsing records and recording behavior data. 　　But if only some of the operational software to analyze, but not how to use logical data analysis, it is also a simple data processing. 　　Rather than being able to go deep into the core of the planning strategy. Of course, basic skills is the most important link, want to become data scientists, for these procedures you should have some understanding ...

With the upsurge of large data, there are flood-like information in almost every field, and it is far from satisfying to do data processing in the face of thousands of users ' browsing records and recording behavior data. But if only some of the operational software to analyze, but not how to use logical data analysis, it is also a simple data processing. Rather than being able to go deep into the core of the planning strategy. Of course, basic skills is the most important link, want to become data scientists, for these procedures you should have some understanding: ...

With the upsurge of large data, there are flood-like information in almost every field, and it is far from satisfying to do data processing in the face of thousands of users ' browsing records and recording behavior data. But if only some of the operational software to analyze, but not how to use logical data analysis, it is also a simple data processing. Rather than being able to go deep into the core of the planning strategy. Of course, basic skills is the most important link, want to become data scientists, for these procedures you should have some understanding: ...

We have seen many of these cases where companies are willing to share their achievements in the use of large data. In any paradigm shift in the IT Industry (Paradigmshift), a specific theme attracts a lot of attention from news media, investors and innovators, a shift that requires strong commercial price support. This typical case is: customer service, distributed computing, and service-oriented architecture and language, such as JAVA. We have also seen a beneficial ecosystem of emergence, rapid praise or expansion capabilities of core support technology in large data cases ...

We have seen many of these cases where companies are willing to share their achievements in the use of large data. In any paradigm shift in the IT Industry (Paradigmshift), a specific theme attracts a lot of attention from news media, investors and innovators, a shift that requires strong commercial price support. 　　This typical case is: customer service, distributed computing, and service-oriented architecture and language, such as JAVA. We have also seen a beneficial ecosystem of emergence, rapid praise or expansion capabilities of the core support technology in large data ...

We have seen many of these cases where companies are willing to share their achievements in the use of large data. In any paradigm shift in the IT Industry (Paradigmshift), a specific theme attracts a lot of attention from news media, investors and innovators, a shift that requires strong commercial price support. This typical case is: customer service, distributed computing, and service-oriented architecture and language, such as JAVA. We have also seen a beneficial ecosystem of emergence, rapid praise or expansion capabilities of core support technology in large data cases ...

The development of big data in 2012 is in full swing, and it is catching up with cloud computing. If we compare this year to the year in which big data takes root, then 2013 will usher in a year of thriving and even blossoming.