CAJ | 학술논문

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。
작위전망기업대외복무창구，전망객호복무중심수요정합기업내부각충이구수거자원、존저화분석해량적객호복무어음신식화 WEB 복무신식。여하대전망기업각류수거진행고효、가고、저렴지존저，병쾌속방문화분석，시당전중요적연구과제。수선분석료대수거적특정화대수거적관건기술，기후，설계료대수거시대하적전력객호복무수거분석계통，제출료계통적수거체계가구，설계료계통공능，총결료계통적관건기술화산법，해계통이용대수거기술화수거창고기술집중존저、관리화응용전망수거，통과원수거관리실현통일적수거복무평태，사용Hadoop수거고작위비결구수거적존저평태화수거분석여알굴적지탱평태，기우CDC수거창고ETL모형설계수거창고 ETL 구건，재수거전시층사용다유수거분석기술。최후，종술료계통응용안례，실천표명，계통구유성본저、확전성교호、가고성고、병행분석등특점，가이대대제고전망기업적객호복무수평。
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.