Big Data Survey Report "Bigdata wave" forces companies to make choices

According to the IDC survey, global electronic device storage data will be 30 times times as fast as 2020, to 35ZB (equivalent to 1 billion 1TB of hard disk capacity). The arrival of large data waves has also brought a new challenge to the enterprise. For the prepared enterprise this is undoubtedly an information gold mine, can reasonably transform large data into valuable information to become the necessary skills of future enterprises. Coincides with this time, CSDN specifically for enterprise-related personnel conducted a large-scale questionnaire survey, and in thousands of of the survey report summed up the current enterprise data business. Here we will also show the results of the survey for your reference.

Data format characteristics in large data age

First, let's take a look at the data format features of the big data age. From an IT perspective, information structure types have roughly gone through three of waves. It must be noted that the new wave does not replace the old wave, which is still evolving, with three types of data structures always exist, but one type of structure is often dominant in other structures:

Structured information-This information can be found in relational databases and has dominated it applications for years. This is the key task OLTP system business depends on the information, in addition, the structure of database information can be sorted and queried;

Semi-structured information-This is the second wave of it, including e-mail, word processing files, and information stored and posted on the web. Semi-structured information is based on content, can be used for search, which is the reason for Google's existence;

Unstructured information-This information can be considered essentially a bit-mapped data in its essential form. Data must be in a perceptible form (such as being able to be heard or seen in audio, video, and multimedia files). Many large data are unstructured, and their sheer size and complexity require advanced analysis tools to create or leverage a structure that is easier to perceive and interact with.

Large-size data processing infrastructure in enterprises is lagging behind

From the results of the survey can be seen, nearly 50% of the number of enterprise servers in 100 units, and 100 to 500 units occupy 22% of the proportion. 500 to 2000 servers occupy the remaining 28.4% percentage. It can be seen that most companies have not yet perfected their hardware infrastructure facilities in the face of big data. With the current situation of large data processing infrastructure in enterprises, 50% of enterprises face the problem of large data processing (small and medium-sized enterprises in the face of the solution to large numbers should follow the collection, import/processing, query, mining process).

But this is only temporary situation, "cheap" server facilities will gradually be phased out with the development of enterprise business history stage, in the future enterprise Infrastructure system hardware selection, multi-core multi-channel processor and SSD and other equipment will become the preferred enterprise. With Facebook's open Compute project setting an example in the industry, open Compute Project uses the open source community concept to improve server hardware and rack design. Its datacenter Pue value is also one of the leading competitors in the industry.

And in the enterprise with large data processing needs of 52.2% of daily data generation under 100GB, the daily data generation 100GB to 50TB occupied 43.5%, and surprisingly, the daily data generation 50TB above also has a share of 4.4%. As data volumes continue to grow, companies will be forced to increase the deployment of infrastructure. Patent costs will continue to increase, and open source technology, which has been saving the continuing patent fees. For enterprises that urgently need to change their traditional it architectures, the integration of traditional structured data and unstructured data has become a matter of concern for all.

(Responsible editor: The good of the Legacy)