It's hard to get big data.

The industry has a wide consensus on the difficulty of large data landing. "We have 7,900 users around the world, more than 1000 users in the Asia-Pacific region, and 150 users in China, and the applications are landing," said the company. "Http://www.aliyun.com/zixun/aggregation/13553.html" >splunk China sales director Hou Hairong said.

Hou Hairong says, why is big data application landing difficult? A big part of the reason is Hadoop, where users are interested in trying out the open source. However, whether map/reduce, or yarn are not so easy to use, data modeling is like a mountain, across the user's front, so that the application is not easy to fall. For Internet enterprises, due to the advantages of talent, still have the ability to overcome difficulties, but for industry/enterprise and other commercial users, technical bottlenecks are not so easy to cross.

Splunk Asia Manager Mayong pointed out that many industry/enterprise users attach great importance to large data, they will first set up a large data department, research large data applications. In this case, he says, applications are often hard to land. Splunk the angle of large data is different, not from large data, but from the problems faced by users, using Splunk large data to solve the problem.

"The domestic understanding of large data, or stay in the primary stage of data." "Hou Hairong said.

According to the introduction, large data applications and data from where, data size, format, etc. without much concern. The focus of large data should be on giving people who need the data, providing important visibility and finding answers quickly. In the past 30, people always use relational database, search and search by SQL, but with the model of large data application, the new distributed database data organization model replaces the relational database, the search engine technology replaces the SQL, so the ability of data analysis and use has made great progress.

Data analysis out of relational database stage

By analyzing the large data of the machine, people can locate the fault quickly, thus reducing the time of MTTR (score time to restoration, the average recovery date), improving the online time and ability of the system, integrating tools, driving innovation through data analysis, and also using the data service business users. Through the machine large data analysis, can enhance the user to the business real-time insight, thus lets the system management from the passive to the active response.

What big data applications bring to US

It is understood that Splunk provides a professional data storage and processing methods, through the search means, users can be the data on the relevance of mining and exploration. The user does not need to model, also does not need to care about map/reduce, the retrieval lets the user direct use, looks for the data, discovers the value which behind the data contains.

Large data analysis allows maintenance from passive to active

Big data is really simple, the key is to find good tools, use tools to mining the value of the data, value in data, not the tool itself. Hou Hairong said that the domestic large data applications need to step out of the primary application phase, needs to get out of the technical attention, focus on the data, so that the data to produce value.

Can't read the machine big data hidden value