Gold Rush Data era: Large value in large data

After cloud computing, the hot word "big Data Age" became the focus of media chasing. So, what is big data, how much data is worth? What are the opportunities and challenges that the big data age will bring to the industry?

The big data age is coming quietly

Not I don't understand, the world changes fast 12,000 years or a floppy disk era, just more than 10 years, hard disk storage capacity from 4GB, 16GB, 32GB quickly climbed to 1TB. Originally only 1.44MB floppy disk in the sense of storage capacity is still quite large, to the present hard disk capacity jumped to 1TB, but feel the storage space stretched, in the end where there is a problem?

Big Data! The words awakened the dream person, the big data age has come quietly. As the social network matures, mobile bandwidth increases rapidly, and cloud computing and IoT applications are richer. More sensor devices, mobile terminals access to the network, resulting in data and rapid growth.

A survey by Unisohereresearch of 531 independent Oracle users found that 90% of businesses were rapidly increasing data volumes, with 16% per cent growing at 50% or more annually. Many companies have felt the impact of runaway data growth on performance, with 87% of respondents blaming the growing volume of data on the decline in application performance. A report by IDC, a research firm, in June 2011 showed that global data volumes had reached 1.8ZB in 2011, up 5 times times in the past 5 years.

What kind of concept is 1.8ZB? First from the binary to read, from our most familiar with the GB start, 1TB (Trillionbyte) =1024GB;1PB (petabyte) =1024TB; 1EB (ExaByte) =1024pb;1zb (zettabyte) =1024 eb;1yb (yottabyte) =1024 zb;1bb (brontobyte) =1024yb.

To describe the amount of 1.8ZB of data directly, if you burn all of this data into a normal DVD, the height of the disc will equate to a half round-trip from Earth to the moon, which is about 720000 miles. Is it scary that every American writes 3 Twitter tweets a minute and keeps writing for 26,976 years? That's not the scariest thing, IDC predicts that global data volumes will double roughly every two years, with 2015 global data reaching nearly 8ZB, to 2020, The world will reach 35ZB.

The most straightforward understanding of the so-called big data is massive data, often used to describe the vast amount of unstructured and semi-structured data that a company creates, which spends a lot of time and money downloading into relational databases for analysis. Research institute IDC believes that a technology to be a large data technology must meet the three "V" conditions described by IBM, namely diversity (produced), high-capacity (Volume) and Time-sensitive (Velocity). Diversity means that data should contain structured and unstructured data; Large capacity means that the amount of data aggregated together for analysis must be very large, and timeliness means that data processing must be fast.

Large value in large data

Now there are a lot of classic cases that benefit from big data analysis. In the field of scientific research, the U.S. Tsunami warning system has been a great relish, last March 11, Japan after the earthquake occurred only 9 minutes, the United States National Oceanic and Atmospheric Administration (NOAA) issued a detailed tsunami warning. NOAA then simulated the real-time data obtained by the ocean sensors, and the tsunami impact model was created on YouTube sites. Large data analysis plays an important role in guiding people to avoid natural disasters effectively.

In the business world, ebay is a good example. ebay defined more than 500 types of data, the customer's behavior tracking analysis, daily processing of data up to 100PB, through accurate analysis of user's shopping behavior, to reduce advertising investment, stabilize high-end sellers, achieve sustained growth.

It is not difficult to see through the above two cases that the value of large data analysis is very large. Along with the traditional business intelligence system to the depth of the application of the expansion, enterprises have gradually entered the era of large data. The traditional standardized, structured data accounted for only about 15%, and 85% of the data came from unstructured data that existed widely in social networks, IoT, E-commerce, etc. The generation of these unstructured data is often accompanied by the emergence and application of new channels and technologies such as social networks, mobile computing and sensors.

The more comprehensive the data the enterprise uses to analyze, the closer the analysis results to the real, and therefore the larger the business value of the data. Large data analysis is an enterprise must face in the future development process, large data analysis means that the enterprise can obtain new insights from these new data, and integrate it with the details of the known business. Only those enterprises that can use these new data forms can build the competitive advantage of sustainable development.

(Responsible editor: The good of the Legacy)