GB/T 42381.63-2023Data quality - Part 63: Data quality management: Process measurement (English PDF)

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.

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.