基于大数据的数据服务应用研究

Research on Data Service Based on Big Data

目前各行业信息系统中数据积累规模迅速增长,传统的数据存储、处理以及应用服务难以适应持续增长的数据应用需求,各级部门无法有效跨单位获取重要数据信息,进而不能帮助上级机关做出重要辅助决策。对此,提出一种适用于行业数据应用的大数据架构设计,具有并行、分布、稳定、高效等技术特点。研究大数据存储与处理技术、大数据查询与分析技术以及大数据可视化技术,建立数据分类目录体系标准与信息交换共享机制,确保多数据采集渠道的大规模数据能够有效整合、有序组织,综合运用数据统计、数据分析、数据挖掘等方法,提炼能够保障服务于指挥决策支持信息知识并形成可视化平台,满足不同指挥层级应用人员便捷、及时地掌握应用信息的保障需求,提升应用行动的快速反应能力。

With the rapid growth of the data accumulation in the information system of the industry,the traditional data storage,processing and application services are difficult to adapt to the data application demand of continuous growth,and the departments cannot effectively obtain important data information across the units,which cannot help the higher authorities to make important auxiliary decision.For this,we present a large data architecture design for industrial data application,which is parallel,distributed,stable and efficient.We study large data storage and processing technology,large data query and analysis technology and large data visualization technology,and establish system standards and information exchange sharing mechanism to ensure that large data collection channels of large-scale data can be effectively integrated,orderly organization,The data statistics,data analysis,data mining and other methods are used to extract knowledge to support command and decision information and form visualization platform,which meets the needs of grasping the application information conveniently and timely in different command level application personnel and enhances rapid response capability of application action.