Why Big Data applications landing hard? The reason is that a large part of Hadoop, the open source user to always try to personally interested. But regardless of Map Reduce, or YARN is not so easy to use, data modeling is like a mountain, lie in front of the user, so that applications do not easily fall.
Big Data landing difficult, there is broad consensus that this industry. "We have 7900 users around the world, with more than 1000 users in the Asia Pacific, there are 150 users in China, the application of these users are landing." Splunk Sales Director for China Houhai Long said.
Why Big Data applications landing hard?
The reason is that a large part of Hadoop, the open source user to always try to personally interested. But no matter Map / Reduce, or YARN is not so easy to use, data modeling is like a mountain, lie in front of the user, so that applications do not easily fall. For Internet companies, due to the personnel on the advantages, there are the ability to overcome difficulties, but for the industry / enterprises and other commercial users, the technical bottleneck is not so easy to cross.
Mak Yong-guang Splunk Manager North Asia pointed out that many industries / businesses for large data very seriously, they will first set up a large sector of data, research big data applications. He said that in this case, the application is often difficult landing. Splunk large angle data is different, not start from big data, but users face problems from the start, the way to solve the problem with Splunk big data.
"Domestic understanding of big data, or stay in the primary stage of big data." Houhai Long said.
According to reports, applications and data come from large data, data size, format, etc. without much concern. Emphasis should be focused on big data to those who need the data provide important visibility, quickly find the answer. In the past 30 years, people have been using a relational database using SQL to retrieve and search; but with the application of large data models, data organization model of the new distributed database instead of the relational database, search engine technology replaces SQL , so that data analysis and the ability to use with very big step forward.
Data analysis out of the relational database stage
By analyzing big data on the machine, one may quickly locate the fault, thereby reducing MTTR (Mean Time To Restoration, the average recovery time before) time; improve uptime and capacity of the system; integration tools; data analysis-driven innovation, but also can data services business users. Big data analysis through the machine, the user can enhance the real-time insights into the business, so that the system management from passive to active response.
Big Data application gives us what
It is understood, Splunk provides professional data storage and processing mode, the user can conduct mining and exploration of the association between data retrieval means. Users do not need modeling, do not need to care about Map / Reduce, allowing users to directly retrieve get started, find the data and found that the value of the hidden behind the data.
Big Data analysis allows maintenance from passive to active
Big Data is actually very simple, the key is to find a good tool to use the value of data mining tools; the value of that data, rather than the tool itself. Houhai Long said the domestic large data applications Come Out of the initial stage of the application, need to get out of technical concerns, will focus on data, so that data generated value.
The machine can not read the hidden value of Big Data
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