Best Programming Language For Data Analysis

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 ...

People will expect you to give up some of the real work, such as programming, as your age increases and your personal conditions are limited. 　　Move to a bigger task, such as managing a team or raising money. This is true in academia, where the "real professor" decides the details, leaving only the "things in the direction". In other words, the organization faces vertical collaboration: Top managers manage some (cheaper) employees in a parallel structure. In research institutions, senior scientists put forward ideas, and the task of junior scientists is to achieve these ideas. Over time, advanced science ...

One of the key decisions faced by enterprises that perform large data projects is which database to use, SQL or NoSQL? SQL has impressive performance, a huge installation base, and NoSQL is gaining considerable revenue and has many supporters. 　　Let's take a look at the views of two experts on this issue. Experts· VOLTDB's chief technology officer, Ryan Betts, says that SQL has won widespread deployments of large companies, and that big data is another area that it can support. Couchba ...

The following small series summarizes 10 best data mining tools for everyone, which can help you analyze big data from various angles and make correct business decisions through data.

This paper is an excerpt from the book "The Authoritative Guide to Hadoop", published by Tsinghua University Press, which is the author of Tom White, the School of Data Science and engineering, East China Normal University. This book begins with the origins of Hadoop, and integrates theory and practice to introduce Hadoop as an ideal tool for high-performance processing of massive datasets. The book consists of 16 chapters, 3 appendices, covering topics including: Haddoop;mapreduce;hadoop Distributed file system; Hadoop I/O, MapReduce application Open ...

Victor Maire-Schoenberg, one of the authors of the Great Data Age: A major change in life, work and thinking, has said that, as telescopes allow humans to perceive the universe, microscopes allow humans to observe microbes, and big data opens up a major transformation of the times. Large data, the most fashionable word in the IT field, is simply the ability to quickly obtain value information from a variety of data. The United States was the first country to discover and use the value of large data science. March 2012, the Obama administration announced the investment of 200 million dollars to pull big data related industry development, will "big data ...

Storing them is a good choice when you need to work with a lot of data. An incredible discovery or future prediction will not come from unused data. Big data is a complex monster. Writing complex MapReduce programs in the Java programming language takes a lot of time, good resources and expertise, which is what most businesses don't have. 　　This is why building a database with tools such as Hive on Hadoop can be a powerful solution. Peter J Jamack is a ...

Translation: Esri Lucas The first paper on the Spark framework published by Matei, from the University of California, AMP Lab, is limited to my English proficiency, so there must be a lot of mistakes in translation, please find the wrong direct contact with me, thanks. (in parentheses, the italic part is my own interpretation) Summary: MapReduce and its various variants, conducted on a commercial cluster on a large scale ...

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: ...