银行业金融机构数据治理指引和DCMM的对比分析

doi:10.11959/j.issn.2096-0271.2020048

Abstract

Abstract:

Recently,data governance got widespread attention of many industries.Some standards and polices had been published from country and industries,these files defined data governance concept and framework and boost data governance industry development.These files were analysed and some differences between them were identified to help people understand the trends and focus of data governance industry.At same time,some suggestions about how to implement DCMM in the bank industry were provided to help banks to better meet regulatory requirement and improve the maturity level of data management ability.

Key words: big data, data quality, data governance, data management capability maturity assessment model, data culture

CLC Number:

TP30

Hong DAI, Qun ZHANG, Haolin LU, Junzhi BIN. Comparative analysis between bank industry data governance guidelines and DCMM[J]. Big Data Research, 2020, 6(5): 118-128.

Figures/Tables 3

References 9

[1]	中华人民共和国国家质量监督检验检疫总局,中国国家标准化管理委员会. 数据管理能力成熟度评估模型[S]. 2018.
	General Administration of Quality Supervision,Inspection and Quarantine of the People’s Republic of China,Standardization Administration. Data management capability maturity assessment model[S]. 2018.
[2]	中国银行保险监督管理委员会. 银行业金融机构数据治理指引[Z]. 2018.
	China Banking and Insurance Regulatory Commission. The 128-bit blockcipher CLEFIA:security and performance evaluations[Z]. 2018.
[3]	中国银行保险监督管理委员会. 银行监管统计数据质量管理良好标准（试行）[Z]. 2011.
	China Banking and Insurance Regulatory Commission. Standard for quality management of bank supervision statistics data (trial)[S]. 2011.
[4]	ENGLISH L . Information quality applied:best practices for improving business information,processes and systems[M]. Indianapolis: WileyPress, 2009.
[5]	Basel Committee on Banking Supervision. Principles for effective risk data aggregation and risk reporting[Z]. 2013.
[6]	彼得·艾肯, 戈曼·戈尔曼, .首席数据官实战:重铸高管团队,充分利用最有价值资产[M]. 刘晨,宾军志,译.北京: 清华大学出版社, 2015.
	PETER A , MICHAEL G . The case for the chief data officer:recasting the c-suite to leverage your most valuable asset[M]. Translated by LIU C,BIN J Z. Beijing: Tsinghua University PressPress, 2015.
[7]	国际数据管理协会. DAMA数据管理知识体系指南[Z]. 2004.
	The Data Management Association. The DAMA guide to the data management body of knowledge[Z]. 2004.
[8]	代红, 张群, 尹卓 . 大数据治理标准体系研究[J]. 大数据, 2019,5(3): 47-54.
	DAI H , ZHANG Q , YIN Z . Study on big data governance standard system[J]. Big Data Research, 2019,5(3): 47-54.
[9]	张群, 吴东亚, 赵菁华 . 大数据标准体系[J]. 大数据, 2017,3(4): 11-19.
	ZHANG Q , WU D Y , ZHAO J H . Big data standards system[J]. Big Data Research, 2017,3(4): 11-19.

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指引	指引中的条例数目/条	对应的DCMM能力域	对应的DCMM能力项	对应DCMM的条例数/条
数据价值实现	12	数据应用	数据分析	5
		数据生存周期	数据需求	1
		无对应	无对应	6
数据治理架构	9	数据治理	数据治理组织、数据治理沟通	8
		数据战略	数据战略规划	1
		无对应	无对应	0
数据质量控制	9	数据质量	数据质量需求、数据质量检查、数据质量提升	5
		数据标准	指标数据	1
		数据治理	数据制度建设	1
		数据应用	无对应	1
		无对应	无对应	1
数据管理	12	数据战略	数据战略规划、数据战略实施、数据战略评估	1
		数据治理	数据制度建设、数据治理组织	3
		数据架构	数据模型、数据集成与共享	2
		数据应用	数据开放共享	1
		数据标准	业务术语、参考数据和主数据、数据源、指标数据	1
		数据安全	数据安全策略、数据安全管理	1
		数据质量	数据质量需求、数据质量检查	1
		数据生存周期	数据退役	1
		无对应	无对应	2

DCMM能力域	DCMM能力项	对应的《指引》条例	对应指引的条例数/条
数据战略	数据战略规划	数据治理架构、数据管理	2
	数据战略实施	数据管理	1
	数据战略评估	数据管理	1
数据治理	数据制度建设	数据质量控制、数据管理	3
	数据治理组织	数据治理架构、数据管理	7
	数据治理沟通	数据治理架构	2
数据应用	数据分析	数据价值实现	5
	数据开放共享	数据管理	1
	数据服务	无对应	0
数据架构	数据模型	数据管理	1
	数据集成与共享	数据管理	1
	元数据管理	无对应	0
	数据分布	无对应	0
数据标准	业务术语
	参考数据和主数据	数据管理、数据质量控制	2
	数据源
	指标数据
数据安全	数据安全策略	数据管理	1
	数据安全管理
	数据安全审计	无对应	0
数据质量	数据质量需求
	数据质量检查	数据质量控制	8
	数据质量分析
	数据质量提升
数据生命周期	数据需求	数据价值实现	1
	数据设计和开发	无对应	0
	数据运维		0
	数据退役	数据管理	1

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Comparative analysis between bank industry data governance guidelines and DCMM

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