Big Data Technologies List

Large data areas of processing, my own contact time is not long, formal projects are still in development, by the large data processing attraction, so there is the idea of writing articles. Large data is presented in the form of database technologies such as Hadoop and "NO SQL", Mongo and Cassandra. Real-time analysis of data is now likely to be easier. Now the transformation of the cluster will be more and more reliable, can be completed within 20 minutes. Because we support it with a table? But these are just some of the newer, untapped advantages and ...

Let's not dwell on how much data a disk can hold or whether it will use Hadoop. 　　The real question about big data is how the business user will use Hadoop, how far our system can go on the intelligent path, and how we're going to make sure it's all under control. Over the past few years, big data technologies have come a long way, from an optimistic and positive buzzword to a difficult illness that people hate, and the focus shifted from sheer data to the pursuit of type and speed. The so-called "big Data" and its related technologies are experiencing ...

2014 is coming soon, according to Business Insider, which of the 2013 's fiery technologies will be hotter next year. Including cloud computing, big data, the rise of tablet computers and the Internet of things. 　　In this respect, market research firm IDC forecasts in detail how these trends will unfold next year and how to generate a huge market of $1 billion trillion. 1, individuals and companies will be in the technology sector next year to spend 2.1 trillion U.S. dollars IDC forecast, global IT sector spending will increase next year 5% to 2.1 trillion dollar market. Personal and ...

The Data Platform Business Unit first used not the MaxCompute (original ODPS) currently in use, but Hadoop. The original Hadoop cluster was named Cloud Ladder 1. At that time, Alibaba was also developing its own computing platform, which was the original ODPS, and named it. Cloud Ladder 2.

Today, big data technologies, especially big data analytics, have evolved into an important part of most corporate strategies, and companies are under intense pressure to keep up with the rapid growth of big data.

Tencent has always regarded big data application as an important development strategy of the company, and based on more than ten years of experience in Internet product development and operation, it has formed a complete, reliable and scalable big data business application framework to provide users with big data processing service.

The hottest science and technology terms for 2013 are none other than "big data," and related books have long dominated the list of bestsellers, giving unprecedented attention to big data. The new ideas brought by big data are gradually penetrating into every industry and changing the way we all think as creators of data. Before the advent of big data, it was a period of rapid development of technologies such as the Internet, cloud computing and Internet of Things. With the popularization and extensive construction of information terminals such as intelligent terminals and digital cities, anyone at any time, anywhere ...

Large data Applications March 2012 The Obama administration issued a "Big data research and development plan". In response, the National Science Foundation, the National Institutes of Health, the Ministry of Defence, the Department of Energy and the United States Geological Survey are investing in big data innovation. Many companies in the United States are conducting their business activities around large data acquisition and utilization capabilities as part of their product or operational backend. Research groups, governments and the private sector are also speeding up the generation of large datasets of various themes, including: Climate change, traffic patterns, health and disease data, buying behavior ...

Currently, the Hadoop-based big data open source ecosystem is widely used. At the earliest, Hadoop was considered to be deployed only in a trusted environment, and as more departments and users joined, any user could access and delete data, putting data at great security risk.

In today's era of big data, businesses can learn more about consumers through a number of channels and can even understand what they need than consumers themselves. But in fact, very few companies really understand the depths of consumers, to give attentive personalized service, the enterprise is not enough intentions or the customer is too picky? In the data age, how companies should be better and faster to meet consumer spending Personal needs, to reach their psychological expectations? In the big data support, the company's personalized service will become more reliable, more popular? The rapid growth of big data and related technologies ...