Shulou(Shulou.com)06/03 Report--

This article is about which three sources of big data are shared with you. The editor thinks it is very practical, so I share it with you to learn. I hope you can get something after reading this article. Let's take a look at it with the editor.

1. Transaction data, including POS machine data, credit card swiping data, etc.

2. Human data, including email, documents, pictures and data streams generated through Wechat, blog, Twitter, etc.

3. Machine and sensor data, such as sensors, gauges and other facilities.

Big data what?

This definition is given for "big data" (Gartner), a research institution of "big data". "big data" needs a new processing model to have stronger decision-making power, insight and process optimization ability to adapt to massive, high growth rate and diversified information assets.

The definition given by the McKinsey Global Research Institute is that the scale of data collection is so large that it is far beyond the capabilities of traditional database software tools in terms of acquisition, storage, management and analysis. it has four characteristics: massive data scale, rapid data flow, diverse data types and low value density.

The strategic significance of big data's technology is not to master huge data and information, but to deal with these meaningful data professionally. In other words, if big data is compared to an industry, the key to profitability of this industry lies in improving the "processing ability" of data and realizing the "value-added" of data through "processing".

Technically, the relationship between big data and cloud computing is as inseparable as the pros and cons of a coin. Big data must not be able to process with a single computer and must adopt a distributed architecture. It is characterized by distributed data mining for massive data. But it must rely on the distributed processing, distributed database, cloud storage and virtualization technology of cloud computing.

With the advent of the cloud era, big data (Big data) has also attracted more and more attention. According to the team of analysts, big data is often used to describe the large amount of unstructured and semi-structured data created by a company that takes too much time and money to download to a relational database for analysis. Big data analysis is often associated with cloud computing because real-time large dataset analysis requires a framework like MapReduce to assign work to dozens, hundreds or even thousands of computers.

Big data needs special techniques to effectively handle large amounts of tolerated data over a period of time. The technologies applicable to big data include massively parallel processing (MPP) databases, data mining, distributed file systems, distributed databases, cloud computing platforms, the Internet and scalable storage systems.

These are the three sources of big data. The editor believes that there are some knowledge points that we may see or use in our daily work. I hope you can learn more from this article. For more details, please follow the industry information channel.

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