Big data main analysis mode and analysis technology

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The main feature of the data analyzed in the era of big data is “multi-source heterogeneity”, and its analysis process is a layer-by-layer abstraction, dimension reduction, generalization and interpretation process. Dividing from the source of data collection, the data objects analyzed and processed in the era of big data can be divided into the following categories:
(1) Internet browsing data, click rate, various social networking sites, changes in dynamic website web content information, search volume of search engines, real-time network monitoring data, and other Internet data.
(2) Log data that can be used to analyze user behavior, operation of the system, and system operating status.
(3) Various signals, signaling data, personal information of the user, and data such as call position and duration in the communication field.
(4) Statistical analysis data of various fields and industries in the national economy.
For these large numbers of unstructured data from different sources. The characteristics of the analysis mode are as follows: For the data generated by the Internet, the main application is to establish a search engine and perform data retrieval and processing through a search engine.
With the continuous development of technology, the introduction of personalized recommendation engine and big data analysis engine can more effectively analyze more valuable information in massive data; for log data, it can run the behavior log and system for users to click browse. The behavior log is analyzed. This allows the system to produce more intelligent results based on actual conditions. The analysis and processing mode of log data and web page data are similar, and the value stored in the data is explored through detailed analysis.
This data analysis processing mode is called "offline batch mode." For data analysis in the communication field, the analysis decision-makers will statistically summarize and query the carefully analyzed data, and obtain valuable information in a short time.
This ensures system interactivity and enhances the user experience. This data analysis processing mode is called the “query analysis” mode; it is called “real-time data analysis and processing” mode for real-time monitoring of data in the Internet and important industries in the national economy.
The above is a data analysis mode based on temporal characteristics. The main methods to achieve these analysis modes are: classification, regression analysis, clustering, association rules, neural network, WEB data mining and so on.
To extract and analyze valuable information from the rapidly growing data resources requires advanced analytical techniques to support it. From a macro perspective, the problems faced by the development of big data analysis technology include three main characteristics:
(1) The amount of data is huge and growing at an alarming rate;
(2) Diversified data types and structures, with semi-structured and unstructured data as the main;
(3) It is necessary to have a timely and rapid analysis speed, that is, real-time analysis. These characteristics make traditional data analysis technology unable to meet the requirements, and a more advanced data analysis platform is a better choice in the era of big data.
In order to effectively cope with the three main characteristics of the data analysis problem in the era of big data and meet the basic needs of big data analysis, the current and future period will mainly use the distributed database or distributed computing cluster to carry on the massive data stored in it. From shallow to deep analysis and subtotals.

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