大数据环境下的电力客户服务数据分析系统

Power Customer Service Data Analysis System in Big Data Environments

作为电网企业对外服务窗口,电网客户服务中心需要整合企业内部各种异构数据资源、存贮和分析海量的客户服务语音信息和WEB服务信息.如何对电网企业各类数据进行高效、可靠、低廉地存储,并快速访问和分析,是当前重要的研究课题.首先分析了大数据的特征和大数据的关键技术,其后,设计了大数据时代下的电力客户服务数据分析系统,提出了系统的数据体系架构,设计了系统功能,总结了系统的关键技术和算法,该系统利用大数据技术和数据仓库技术集中存储、管理和应用电网数据,通过元数据管理实现统一的数据服务平台,使用Hadoop数据库作为非结构数据的存贮平台和数据分析与挖掘的支撑平台,基于CDC数据仓库ETL模型设计数据仓库ETL构件,在数据展示层使用多维数据分析技术.最后,综述了系统应用案例,实践表明,系统具有成本低、扩展性较好、可靠性高、并行分析等特点,可以大大提高电网企业的客户服务水平.

As an external service window of power grid enterprise, the customer service center needs to integrate heterogeneous data sources within the enterprise, storage and analysis vast amount of customer service voice information and WEB service information. Hence, it becomes a very important topic on how to carry out the way to store various types of data in power grid efficiently, reliably, inexpensively and with availability of quick access and analysis. We have analyzed the key features and key technologies of big data, and designed the customer service data analysis system for power enterprises under big data Era. This paper covers data architecture, major system functions, key techniques and algorithms of the system. The system is designed on top of big data technology and data warehouse technology to centralized store, manage and use data, to achieve a unified data services platform through metadata management. The system is using Hadoop database for unstructured data storage, which works as data analysis and mining support platform as well. The data warehouse ETL component is designed based on CDC data warehouse ETL model, while the data presentation layer is using multidimensional data analysis techniques. Furthermore, the paper includes case review of the system which proves that the system is low cost with better scalability, reliability and parallel analysis features, etc. It may greatly improve the customer service level of power grid enterprise.