ybstrong的专栏

数据治理的框架介绍。Data complexity and volume continue to explode; businesses have grown more sophisticated in their use of data which drives new demands that require different ways tocombine, manipulate, store,and present information. Forward thinking companies have recognised that data management solutions on their own are becoming very expensive and not able to cope with business reality, and thatthey need to solve the data problem in a different way through the implementation of effective data governance. Attempts in governing data failed before, as they were driven by IT, and affected by rigid processes and fragmented activities carried out on system-by-system basis. Up to very recently governance is mostly informal, in siloes around specific enterprise repositories, lacking in structure and the in wider support by the organisation. With the emergence of cloud computing and the increased adoption, data governance is receiving an increasing interest amongst specialist, but still under researched. This paper presents initial research towards developing an effective datagovernance programmes for the cloud paradigm. The paper discusses why it is essential to do so from both the cloud consumer and provider perspectives and proposes a conceptual framework and a five-step procedure for designing data governance for cloud computing.

分析了中国交通运输数据标准的编制现状和管理现状，将交通运输数据标准分为管理标 准、数据定义标准、交换标准和接口实现标准４类。分析了数据在产生、存储、交换以及应用环节的 标准化需求，并与编制现状进行了对比分析。论述了交通运输数据标准管理和总体规划、数据定 义、数据存储、数据交换和决策支持应用５方面的标准研究现状以及存在的不足。分析结果表明： 当前标准管理和总体规划主要采用自下而上和标委会分别负责的模式，存在标准归口重叠和总体 规划研究不足的问题。在数据定义标准方面，现有基础标准过于强调满足应用系统的需要，使得基 础标准的基础性不足，造成数据定义标准缺乏体系。在数据存储方面，数据存储标准的研究制定尚 属空白。在数据交换方面，各业务系统已经制定一些内部标准，但尚缺乏一种开放的、系统的共享 和交换机制。在决策支持应用方面的研究缺乏针对准确数据、大数据的决策支持方法。建议成立 交通信息基础性标准工作组，加强数据标准的总体规划研究并协调标委会之间的工作；在标准建设 方面应加强顶层设计；同时应加强交通运输决策支持方法研究。

社交网络海量数据的分析与可视化，对于大数据的分析很有用

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C语言函数速查 包含程序员的一些常用函数。。。。。。。