Big Data Reporting Tools

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.

"Editor's note" This article is reproduced in the public number "Fu Zhihua", the author has been Tencent social networking business Group data center director and Tencent Data Association president.     Before Tencent, he worked in the market consulting, Analysys International, China Internet Association, and served as vice president of Dcci Internet Data Center. The internet industry in the accumulation of large data and applications to Baidu, Tencent and Alibaba is the most noteworthy. Baidu, Tencent and Alibaba in the application of large data although there is a common place, but due to their respective data sources and ...

What's the big data? Why use large data? What are the popular tools for big data? This article will answer for you. See the original: Get the Complete Story with large data analytics Author: Kayden Kelly Now, Big data is an abused buzzword, but its real value even a small business can achieve. By consolidating data from different sources, such as web analytics, social data, users, and local data, large data can help you understand the overall situation. Large Data Analysis ...

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 ...

In 2014, Ma Yun once again proposed that "human beings are moving from the IT era to the DT era." Humans have moved from the IT era to the DT era. The IT era is dominated by self-control and self-management, while in the DT (Datatechnology) era, it is a service.

Cady Wang (Wang Nanan) you want to know big data, but don't know the jerky terminology? Do you want to know the market and application of large data, but there are no good cases and explanations? 　　Don't worry, this little book from the Wikibon community wants to help you. 　　Yes, this is a small book rather than an article, because it is detailed and meticulous to let you from a completely do not understand the large data technology and related applications of the layman to become a familiar with its concept and meaning of the "inner pedestrian", so it is great! Translator Cady Wang Nanan spent a lot of effort to translate this small book, insufficient ...

With the maturity of large data and predictive analysis, the advantage of open source as the biggest contributor to the underlying technology licensing solution is becoming more and more obvious. Now, from small start-ups to industry giants, vendors of all sizes are using open source to handle large data and run predictive analytics. 　　With the help of open source and cloud computing technology, startups can even compete with big vendors in many ways. 　　Here are some of the top open source tools for large data, grouped into four areas: data storage, development platforms, development tools, and integration, analysis, and reporting tools. Data storage: Apache H ...

Choosing new hardware, storage, and other datacenter infrastructures for large data is a new challenge for IT professionals. Large data is unstructured information with unprecedented scale and form. It includes video, images, and semi-structured data (such as e-mail and text that is common on the web). 　　With more and more sensor-based mobile web monitoring devices and output data, the amount of data available continues to grow exponentially. The pressure to implement big data strategies often comes from the top, because managers believe that companies that can effectively use data will have greater advantages than those who are lagging behind ...

When large data, namely big and cloud computing, mobile applications and social networks, became popular in the 2012, it was the most fashionable word in the field of information technology. IBM, Oracle, SAP, Microsoft and other vendors, like the search for a new gold mine, began to strongly promote the big data concept. As a result, many vendors flocked to grab the big data market, especially SAP's Hana and Oracle's exalytics. In contrast, some of the companies that push bi are not up to the level of large data, sticking to the position of the report analysis. In fact, big data really has ...

Big Data has developed into a critical phase. By 2017, the big data market will have grown to 50 billion dollars, but unfortunately 55% of the big data projects have failed. With the opportunity is the hype and false information, we are in the large data of the West drought stage. 　　The big data industry is in a bit of a stalemate: people who understand it invest in the industry to collect, store and benefit from large data, while others pay for it with a dubious attitude and wonder how big data will affect their business. Benign failure Big data allow error ...