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GB/T 42381.63-2023: Data quality - Part 63: Data quality management: Process measurement
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Data quality - Part 63: Data quality management: Process measurement
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GB/T 42381.63-2023
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Basic data | Standard ID | GB/T 42381.63-2023 (GB/T42381.63-2023) | | Description (Translated English) | Data quality - Part 63: Data quality management: Process measurement | | Sector / Industry | National Standard (Recommended) | | Classification of Chinese Standard | N10 | | Classification of International Standard | 25.040.40 | | Word Count Estimation | 29,230 | | Date of Issue | 2023-09-07 | | Date of Implementation | 2024-04-01 | | Issuing agency(ies) | State Administration for Market Regulation, China National Standardization Administration | GB/T 42381.63-2023: Data quality - Part 63: Data quality management: Process measurement---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 63.Data Quality Management.
process measurement
(ISO 8000-63.2019,IDT)
Published on 2023-09-07
2024-04-01 Implementation
State Administration for Market Regulation
Released by the National Standardization Administration Committee
Table of contents
Preface III
Introduction IV
1 Scope 1
2 Normative reference documents 1
3 Terms and Definitions 1
4 Abbreviations 1
5 Basics of Process Measurement 2
6 Process Measurement and Maturity Model 2
7 Inspection Plan 4
7.1 Overview of inspection plan 4
7.2 Measurement stack structure 4
7.3 Objective 4
7.4 Sub-goal 5
7.5 Question 5
7.6 Indicator 5
7.7 Measurement 5
7.8 Measuring the logical consistency of the stack5
7.9 The role of value evaluation rules in process measurement 6
7.10 Develop a measurement stack using a specific maturity model7
7.11 Implement process measurement 7
Appendix A (Informative) Document Identification 11
Appendix B (Informative) Reference Table 12 for specific process assessment models
Appendix C (Informative) Data Quality Management Measurement Stack Example 14
Appendix D (informative) Example 17 of process assessment based on ISO /IEC 33020
Appendix E (informative) Example of how to define measurement data quality process characteristics 20
Reference 22
Foreword
This document complies with the provisions of GB/T 1.1-2020 "Standardization Work Guidelines Part 1.Structure and Drafting Rules of Standardization Documents"
Drafting.
This document is Part 63 of GB/T 42381 "Data Quality". GB/T 42381 has released the following parts.
---Part 8.Information and data quality. Concepts and measurements;
---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 120.Master data. Characteristic data exchange. Traceability;
---Part 130.Master data. Characteristic data exchange. Accuracy;
---Part 140.Master data. Characteristic data exchange. Integrity.
This document is equivalent to ISO 8000-63.2019 "Data Quality Part 63.Data Quality Management. Process Measurement".
Please note that some content in this document may be subject to patents. The publisher 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 was drafted by. China Institute of Standardization, Chongqing Dongke Mold Manufacturing Co., Ltd., Kunming Shipbuilding Intelligent Technology Co., Ltd., Nuo
Li Intelligent Equipment Co., Ltd., Tianneng Saft Energy Co., Ltd., Sanmen Sanyou Technology Co., Ltd., Shanxi Yangmei Chemical Industry
Machinery (Group) Co., Ltd., Beijing Jingyi Automation Equipment Technology Co., Ltd., Nanjing Panda Electronic Equipment Co., Ltd., Hangzhou Shenhao
Technology Co., Ltd., Institute of Computing Technology, Chinese Academy of Sciences, Hangzhou Dechuang Energy Equipment Co., Ltd., Hangzhou Sikan Technology Co., Ltd.,
Xiamen Aipusheng Electronic Technology Co., Ltd., Liaocheng Jixing New Energy Technology Co., Ltd., Zhejiang Zhongchai Machinery Co., Ltd., Ningbo Zhonghuanzhi
Intellectual Property Rights Co., Ltd., Shandong Hada Electric Co., Ltd., Dalian Haosen Equipment Manufacturing Co., Ltd., China Southern Power Grid Peak Regulation and Frequency Modulation Power Generation Co., Ltd.
Co., Ltd. Information and Communication Branch, Shenzhen Zhongyan Plastic Technology Co., Ltd., Chongqing Yuxin Door Industry Co., Ltd., Qingyan Xunke (Beijing) Technology Co., Ltd.
Co., Ltd., Wuhu Tianhang Equipment Technology Co., Ltd., Tangshan Longquan Machinery Co., Ltd., Shanxi Ruiseke Environmental Protection Technology Co., Ltd., Tianshui Tianguang
SEMICONDUCTORS LIMITED.
The main drafters of this document. Wang Zhiqiang, Yang Qinghai, Xu Kaicheng, Yang Senyu, Yue Hua, Li Wenzhong, Zhou Yinmei, Xu Songyi, Wang Guibo,
Gu Xiandai, Gong Li, Tian Shaohua, Yu Hao, Zhu Xinrong, He Mengxing, Cao Ketao, Cao Guangke, Hong Xuehai, Niu Weijie, Lin Haihan, Wang Jiangfeng, Li Xingze,
Cai Jiajun, Yao Bin, Zhao Jing, Wang Xuan, Zhong Jianxu, Zhao Ruixiang, Li Wei, Xu Kaisong, Xue Ruide, Lu Yu, Yue Gaofeng, Wen Na, Gao Liang.
Introduction
Create, collect, store, maintain, transmit, process and present information and data to support business processes in a timely and cost-effective manner, which requires solving
Determine the relevant characteristics of information and data quality, and also need to measure, manage and report information and data quality.
GB/T 42381 defines the relevant characteristics that determine information and data quality, and provides methods for managing, measuring, and improving information and data quality.
Methods. These given methods can be used to assess the quality of information and data. expectations and requirements for a given approach, oriented to the current business case
Making cuts is also important.
GB/T 42381 includes parts that apply to all data types, as well as parts that apply to specific data types. GB/T 42381 both
It can be used independently or in conjunction with a quality management system.
GB/T 42381 "Data Quality" consists of the following series.
---Part 1~Part 99.Overview of data quality. This series gives the structure of the data quality standard series, which covers
Comprehensive content including basic concepts, data quality management, and data quality assessment.
---Part 100~Part.199.Master data quality. Master data describes individuals, organizations, locations, items, services, processes, rules and
standard. This family of standards describes the characteristics that define the quality of master data. These features include. semantics, grammatical encoding, consistency of requirements
integrity, data provenance, accuracy, completeness and data governance. This series of standards specifies some master data information that is used in the overall
to ensure the reliability of data communication between the information sender and the receiver.
---Part.200~Part 299.Transaction data quality. Transaction data describes time events, including individuals, organizations, locations, items,
Services, processes, rules and standards. This family of standards describes the characteristics that define transactional data quality. These features include. semantics, language
Legal coding, consistency of requirements, data provenance, accuracy, completeness and data governance. This series of standards specifies some business matters
Service data information, which generally ensures the reliability of data communication between the information sender and the receiver.
---Part 300~Part 399.Product data quality. Product data quality is a measure of the correctness and applicability of product data. Product
Data can ensure that the data can be provided to users who need the data in a timely manner. Product data is the data needed for products from concept to manufacturing.
according to. Therefore, products include not only computer-aided design (CAD) data, but also computer-aided manufacturing (CAM), computational data
Engineering (CAE) data, product data management (PDM) data, and other types of data. The main intention of this series of standards
It is to improve the efficiency of coordinated product development by reducing duplication of work on the data receiving end.
GB/T 42381 "Data Quality" is intended to consist of the following parts.
---Part 1.Overview. The purpose is to explain the scope and structure of GB/T 42381 (all parts), and to explain GB/T 42381
Relationship to other standards.
---Part 2.Terminology. The purpose is to provide terminology and vocabulary used in GB/T 42381 (all parts).
---Part 8.Information and data quality. Concepts and measurements. The purpose is to illustrate the measurement when performed in quality management processes and systems
Prerequisites for information and data quality.
---Part 51.Data Governance. Policy Statement for Data Exchange. The purpose is to support data governance policy statement exchange and automated testing.
Test whether the data set meets the requirements of the policy statement.
---Part 61.Data Quality Management. Process Reference Model. The purpose is to describe the model's ability to support assessment and improvement processes,
and increase organizational maturity in data quality management.
---Part 62.Data quality management. Organizational process maturity assessment. Application of relevant standards for process assessment. The purpose is to describe the group
How organizations use the maturity model to assess the maturity of their processes related to data quality management specified in GB/T 42381.61.
---Part 63.Data quality management. process measurement. The purpose is to specify a process suitable for use when assessing process maturity.
process measurement method.
---Part 65.Data quality management. Process measurement scales. The aim is to develop a simple measurement method to assess organizational performance
implementation of data quality management.
---Part 66.Data quality management. Evaluation indicators for data processing in production operations management. The purpose is to identify the factors that arise in a manufacturing organization
Process maturity for data quality management of production operations management data.
---Part 81.Data Quality Assessment. Data Collection. The purpose is to apply analytical techniques to the element analysis of data in practical use.
analysis method.
---Part 82.Data Quality Assessment. Creating Data Rules. The purpose is to specify how different data rules apply to various classes
type of data.
---Part 100.Master Data. Characteristic Data Exchange. Overview. The purpose is to provide an introduction to master data, the data architecture of master data, and high-level
level data model and a description of each part in the group.
---Part 110.Master data. Characteristic data exchange. syntax, semantic encoding and conformance to data specifications. The purpose is to provide
Requirements that computers can check to exchange master data consisting of characteristic data.
---Part 115.Master data. Quality identifier exchange. Syntax, semantics and parsing requirements. The purpose is to provide components for the exchange of master data
Requirements for identifiers of various parts.
---Part 116.Master data. Quality identifier exchange. Application of ISO 8000-115 authorized entity identifiers. The purpose is to express
Authorized Legal Entity Identifier (ALEI) requirements.
---Part 120.Master data. Characteristic data exchange. Traceability. The purpose is to describe the source of master data consisting of characteristic data
Requirements for the presentation and exchange of information.
---Part 130.Master data. Characteristic data exchange. Accuracy. The purpose is to provide an accurate view of the master data consisting of characteristic data
Sexual expressions and requirements for the exchange of information.
---Part 140.Master data. Characteristic data exchange. Integrity. The purpose is to provide a complete view of the master data consisting of characteristic data
Representation and exchange of sexual information.
---Part 150.Master Data. Quality Management Framework. The purpose is to provide groups with appropriate roles and responsibilities for data quality management.
Key considerations for weaving.
---Part 210.Sensor data. Data quality characteristics. The aim is to provide a qualitative characterization of the discrete data recorded by the sensor.
---Part 311.Product Data Quality (PDQ-S) Application Guide for Shape. The purpose is to analyze product data about shape
Guidance is provided on the application of quality (PDQ-S).
This document is Part 63 of GB/T 42381 "Data Quality", which can be used alone or in combination with other parts.
This document only corrects data nonconformities, and the improvement in data quality is limited because the nonconformities will reoccur. However, through data quality
The process tracks and corrects the root causes of unqualified data and related data, which can prevent the recurrence of similar data unqualified. Therefore, a
A process-centric data quality management framework to improve data quality more effectively and efficiently. In addition, through the process of evaluation and change
Improve data quality by assessing underperforming processes identified during the assessment.
This document identifies a process measurement method suitable for use when assessing process maturity. When organizations want to improve data quality management
This method can be used when the level of maturity is high.
This document is intended for use by actors who benefit from information or data quality, focusing on one or more information issues between and within organizations.
information system, running through all stages of the data life cycle.
Appendix A provides an identifier that can be used to unambiguously identify this document in open information systems.
Data Quality Part 63.Data Quality Management.
process measurement
1 Scope
This document specifies the structure of a process measurement stack that organizations can use to measure the characteristics of data quality management processes through examples. The structure
It consists of goals, sub-goals, questions, indicators and measures. The instantiation stack consists of content consisting of a maturity assessment model for the selected process
Decide.
The following content falls within the scope of this document.
---Basics of process measurement;
---The inspection plan and inspection order based on which the measurement is performed;
---Measure the structure of the stack;
---The role of the selected maturity model in the instantiation stack.
The following content is outside the scope of this document.
---Methods to verify the executed process;
---Methods to generate measured values from process inspections;
---How to choose an appropriate maturity model.
This document can be used alone or in conjunction with quality management system standards.
Note. GB/T 42381.8 specifies concepts and methods for measuring information and data quality.
2 Normative reference documents
The contents of the following documents constitute essential provisions of this document through normative references in the text. Among them, the dated quotations
For undated referenced documents, only the version corresponding to that date applies to this document; for undated referenced documents, the latest version (including all amendments) applies to
this document.
ISO 8000-2 Dataquality-Part 2.Vocabulary
3 Terms and definitions
The terms and definitions defined in ISO 8000-2 apply to this document.
The ISO and IEC terminology databases are accessed via.
The following abbreviations apply to this document.
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