A multi-dimensional real-time clustering analysis method based on big data and any customer group

A technology of cluster analysis and big data, applied in other database retrieval, other database query, other database browsing/visualization, etc., can solve the problems of short time, complicated data acquisition process, and inability to meet business needs.

Pending Publication Date: 2019-05-03
南京安讯科技有限责任公司
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  • Abstract
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  • Claims
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AI Technical Summary

Problems solved by technology

[0004] In order to keep up with the rapid development of the times, the business is constantly updated and iterated, resulting in rapid changes in business indicators. In order to be able to comprehensively and quickly grasp relevant information, the product managers and business personnel in charge of the business need the manual support of many analysts and the IT department. Support, the process of obtaining data is complicated and takes a long time
Due to the rapid changes in the business, the analysis report obtained based on the cluster analysis calculation does not meet the business needs for a short time, and needs to be redeveloped

Method used

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  • A multi-dimensional real-time clustering analysis method based on big data and any customer group
  • A multi-dimensional real-time clustering analysis method based on big data and any customer group
  • A multi-dimensional real-time clustering analysis method based on big data and any customer group

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Embodiment Construction

[0030] like figure 1 As shown, the present invention is based on a method for multi-dimensional real-time cluster analysis of any customer group of big data, which is characterized in that it comprises the following steps:

[0031] Step 1: Preprocess the data source, label the data and configure the visualization.

[0032] The data source is stored in a SparkSQL distributed cluster. According to business needs such as an indicator increase, ARPU increase, package migration, etc., confirm the multi-dimensional data analysis and confirm the data source for access.

[0033] The preprocessing of data sources includes data cleaning and data labeling. The data cleaning is ETL processing, that is, data extraction (extract), interactive transformation (transform), and loading (load) to form high-value quasi-real-time data labels.

[0034] Step 2: Configure the analysis dimension for the labeled data.

[0035] Analysis dimension configuration includes label layered visualization conf...

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Abstract

The invention relates to a big data-based arbitrary customer group multi-dimensional real-time clustering analysis method, which comprises the following steps of: preprocessing a data source, labelingthe data and carrying out visual configuration; carrying out analysis dimension configuration on the labeled data; determining an analysis index of the analysis dimension and a target customer groupneeding to be analyzed in real time; and performing clustering analysis calculation according to the analysis index and the target customer group, and performing visual display on an analysis result.The method can achieve the real-time analysis of the target customer group, and meets the requirement for accurate subdivision of the customer group required by the rapid change of the service.

Description

technical field [0001] The invention relates to a method for multi-dimensional real-time cluster analysis of arbitrary customer groups based on big data. Background technique [0002] In the era of big data, data is expanding rapidly, and it determines the future development of enterprises. As time goes by, people will become more and more aware of the importance of data to enterprises. To make good use of big data to improve productivity for enterprises, a set of professional analysis tool platform is very necessary. Use statistical analysis methods to extract useful information and form conclusions to study and summarize data in detail. [0003] The arrival of the Internet + era and the arrival of new retail have broken the original business model of many enterprises. Relying on the Internet, enterprises have upgraded the production, circulation and sales process of commodities by using advanced technologies such as big data and artificial intelligence. It is a new retail...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/904G06F16/903G06K9/62
Inventor 饶翔李红颖
Owner 南京安讯科技有限责任公司
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