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Delivery: <= 4 days. True-PDF full-copy in English will be manually translated and delivered via email. GB/T 42381.61-2023: Data quality - Part 61: Data quality management: Process reference model Status: Valid
Basic dataStandard ID: GB/T 42381.61-2023 (GB/T42381.61-2023)Description (Translated English): Data quality - Part 61: Data quality management: Process reference model Sector / Industry: National Standard (Recommended) Classification of Chinese Standard: N10 Classification of International Standard: 25.040.40 Word Count Estimation: 22,240 Date of Issue: 2023-03-17 Date of Implementation: 2023-10-01 Issuing agency(ies): State Administration for Market Regulation, China National Standardization Administration GB/T 42381.61-2023: Data quality - Part 61: Data quality management: Process reference model---This is a DRAFT version for illustration, not a final translation. Full copy of true-PDF in English version (including equations, symbols, images, flow-chart, tables, and figures etc.) will be manually/carefully translated upon your order.ICS 25.040.40 CCSN10 National Standards of People's Republic of China Data quality Part 61.Data quality management. process reference model (ISO 8000-61.2016, IDT) Released on 2023-03-17 2023-10-01 implementation State Administration for Market Regulation Released by the National Standardization Management Committee table of contentsPreface I Introduction II 1 Scope 1 2 Normative references 1 3 Terms and Definitions, Abbreviations 1 3.1 Terms and Definitions 1 3.2 Abbreviations 1 4 Basic principles of data quality management 2 5 Data Quality Management Process 2 5.1 Basic structure of the data quality management process 2 5.2 Detailed structure of the data quality management process3 5.3 Elements of Process Description 4 6 Execute process 4 6.1 Overview 4 6.2 Data Quality Planning 5 6.3 Data Quality Control 7 6.4 Data Quality Assurance 8 6.5 Data Quality Improvement 10 7 Data related support processes 11 7.1 Overview 11 7.2 Data Architecture Management 11 7.3 Data transmission management 12 7.4 Data operation management 12 7.5 Data security management 12 8 Resource provisioning process 13 8.1 Overview 13 8.2 Data Quality Organizational Management 13 8.3 Human resource management 13 9 The relationship between data quality management and data governance14 10 Implementation Requirements 14 Appendix A (Normative) Document Identification 15 Reference 16forewordThis document is in accordance with the provisions of GB/T 1.1-2020 "Guidelines for Standardization Work Part 1.Structure and Drafting Rules for Standardization Documents" drafting. This document is part 61 of GB/T 42381 "Data Quality". GB/T 42381 "Data Quality" has published the following parts. --- Part 8.Information and data quality. concepts and measurements; --- Part 61.Data Quality Management. Process Reference Model. This document is equivalent to ISO 8000-61.2016 "Data Quality Part 61.Data Quality Management. Process Reference Model". The following minimal editorial changes have been made to this document. --- Added a normative reference to Appendix A in Chapter 1; --- Increase PDCA in 3.2. Please note that some contents of this document may refer to patents. The issuing agency of this document assumes no responsibility for identifying patents. This document is proposed by China Machinery Industry Federation. This document is under the jurisdiction of the National Automation System and Integration Standardization Technical Committee (SAC/TC159). This document is drafted by. China National Institute of Standardization, Renmin University of China, Guangzhou Keli New Energy Co., Ltd., Chinese Academy of Sciences Computing Technology Research Institute, Shenzhen Kejiada Technology Co., Ltd., Guangdong Huachang Group Co., Ltd., Guangdong Bangsheng Beidou Technology Co., Ltd., Shenzhen City Panding Technology Co., Ltd., Guangdong Weiheng Power Transmission and Transformation Engineering Co., Ltd., Computer Network Information Center of the Chinese Academy of Sciences, Zhejiang University, Hangzhou Shenhao Technology Co., Ltd., Xi'an Fast Auto Transmission Co., Ltd., Chongqing Military Industry Group Co., Ltd., Nanjing Panda Electronics Co., Ltd. Equipment Co., Ltd., Shenzhen Pengrui Information Technology Co., Ltd. The main drafters of this document. Yang Qinghai, Wang Zhiqiang, An Xiaomi, Hu Long, Hong Xuehai, Ao Wenke, Gu Fu, Guo Jialin, Deng Weiai, Wei Jichao, Liao Zhipeng, Hu Lianglin, Li Yongyue, Yu Zhonghua, Ren Xusheng, Deng Chengcheng, Zhang Weiqun, Han Ning, Lei Bo, Zhang Liuxin, Ying Zhongwen, Luo Renhu, Hong Yan, Liu Shouhua, Xu Kaicheng, Yin Shurui.IntroductionCreating, collecting, storing, maintaining, transmitting, processing, and presenting information and data to support business processes in a timely and cost-effective manner requires addressing To define relevant characteristics of information and data quality, it is also necessary to measure, manage and report information and data quality. GB/T 42381 defines the relevant characteristics that determine the quality of information and data, and provides management, measurement, and improvement of information and data quality Methods. These given methods can be used to assess the quality of information and data. Oriented to the expectations and needs of the current business case, for a given method It's also important to do some tailoring. GB/T 42381 includes sections applicable to all data types, as well as sections applicable to specific data types. GB/T 42381 can It can be used independently or in combination with the quality management system. GB/T 42381 "Data Quality" consists of the following series. --- Parts 1 to 99.Overview of data quality. This series gives the structure of the data quality series standard, data quality standard involves The basic concept of data quality management, data quality assessment and other comprehensive content, ISO 8000-1 gives the data quality part review. --- Parts 100 to.199.Master Data Quality. Master data describe persons, organizations, places, objects, services, processes, rules and allow. This family of standards describes the characteristics that define the quality of master data. These properties include. semantics, syntactic encoding, consistency of requirements, Data provenance, accuracy, integrity and data governance. This series specifies some master data information, which should be identified in general Ensure the reliability of data communication between the information sender and the receiver. ISO 8000-100 gives an overview of the quality part of master data. --- Parts.200 to 299.Transactional data quality. Transactional data describe temporal events, including individuals, organizations, places, objects, services services, processes, rules and standards. This family of standards describes characteristics that define the quality of transactional data. These features include. semantics, syntax Coding, consistency of requirements, data provenance, accuracy, completeness, and data governance. This series specifies some business transaction data information, which should generally ensure the reliability of the data communication between the information sender and the receiver. ISO 8000-200 gives An overview of the transactional data quality section. --- Parts 300 to 399.Product data quality. Product data quality is a measure of the correctness and applicability of product data. The data can ensure that the data can be provided to users who need the data in a timely manner. Product data is the data required by the product from concept to manufacturing. according to. Product data includes computer-aided design (CAD) data, but also computer-aided manufacturing (CAM), computational data tool engineering (CAE), product data management (PDM) data, and other types of data. The main intent of the series is to improve coordination Improve the efficiency of product development and reduce duplication of work at the data receiving end. ISO 8000-300 gives the quality part of product data review. GB/T 42381 "Data Quality" is proposed to consist of the following parts. --- Part 1.Overview; --- Part 2.Terminology; --- Part 8.Information and data quality. concepts and measurements; --- Part 51.Data governance. policy statement for data exchange; --- Part 61.Data quality management. Process reference model; --- Part 62.Data quality management. Organizational process maturity assessment. Application of relevant standards for process assessment; --- Part 63.Data quality management. process measurement; --- Part 65.Data quality management. process measurement scale; --- Part 66.Data quality management. evaluation indicators for production operation management data processing; --- Part 81.Data quality assessment. data collection; --- Part 82.Data quality assessment. Create data rules; --- Part 100.Master data. Feature data exchange. Overview; --- Part 110.Master data. characteristic data exchange. syntax, semantic coding and compliance with data specifications; --- Part 115.Master data. quality identifier exchange. syntax, semantics and parsing requirements; --- Part 116.Master Data. Quality Identifier Exchange. Application of ISO 8000-115 Authorized Entity Identifier; --- Part 120.Master data. characteristic data exchange. traceability; --- Part 130.Master data. characteristic data exchange. accuracy; --- Part 140.Master data. Characteristic data exchange. Integrity; --- Part 150.Master data. quality management framework; --- Part 210.Sensor data. data quality characteristics; --- Part 311.Shape Product Data Quality (PDQ-S) Application Guidelines. This document is Part 61 of GB/T 42381 "Data Quality", which can be used alone or in combination with other parts. Only data nonconformities are corrected, with limited improvement in data quality, as nonconformities will recur. However, tracking through the data quality process And correct the root cause of data failure and related data, can prevent similar data failure from happening again. Therefore, a previous Process-centric data quality management framework to improve data quality more effectively and efficiently. In addition, evaluation processes and improvements can be made Improving data quality by identifying bad processes through estimation. Data quality Part 61.Data quality management. process reference model1 ScopeThis document specifies the processes required for data quality management. Every process is defined by objectives, outcomes and activities, which and activities will be applied to data quality assurance. The following are within the scope of this document. ---Basic principles of data quality management; --- The structure of the data quality management process; --- Definition of data quality management sub-process; --- the relationship between data quality management and data governance; --- Implementation requirements. The following are outside the scope of this document. --- Detailed methods or procedures for achieving established process results. This document applies to the management of the quality of digitized datasets, which include not only structured data stored in databases, but also Includes unstructured data such as images, audio, video, and electronic documents. This document can be used by organizations that manage data quality at the organizational level, e.g. As used in situations where data is being shared and exchanged due to multiple software applications. Internal and external parties, including certification bodies, use this document as a process reference model to assess process capability for data quality management. capacity or organizational maturity, and improve data quality through process improvement. This document can be used in conjunction with quality management system standards (such as ISO 9001) or independently. Appendix A specifies the identification of this document in the information system.2 Normative referencesThe contents of the following documents constitute the essential provisions of this document through normative references in the text. Among them, dated references For documents, only the version corresponding to the date is applicable to this document; for undated reference documents, the latest version (including all amendments) is applicable to this document. ISO 8000-2 Data Quality Part 2.Terminology (Dataquality-Part 2.Vocabulary) 3 Terms and definitions, abbreviations 3.1 Terms and Definitions The terms and definitions defined in ISO 8000-2 apply to this document. 3.2 Abbreviations PDCA. planning, implementation, inspection, disposal (Plan, Do, Check, Act) ......Tips & Frequently Asked Questions:Question 1: How long will the true-PDF of GB/T 42381.61-2023_English be delivered?Answer: Upon your order, we will start to translate GB/T 42381.61-2023_English as soon as possible, and keep you informed of the progress. The lead time is typically 2 ~ 4 working days. The lengthier the document the longer the lead time.Question 2: Can I share the purchased PDF of GB/T 42381.61-2023_English with my colleagues?Answer: Yes. 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