Data Quality Framework
The Data Quality Framework (DQF) provides an industry-developed best practices guide for the improvement of data quality and allows companies to better leverage their data quality programmes and to ensure a continuously-improving cycle for the generation of master data. It details the crucial processes and capabilities that help organisations improve their data quality and maintain a sustainable good quality data output.
What is the GS1 Data Quality Framework?
The GS1 Data Quality Framework is a “best practice” guide for data quality that can be used collaboratively by trading partners.
It consists of several chapters: The core of the document is the Data Quality Management System (DQMS). This chapter describes how an organisation can effectively manage its data, being able to publish good quality data. It is based on best practices of the industry.
Besides the DQMS the Data Quality Framework contains tools that allow organisations to self-assess their processes and their compliance to the recommended best practices of a DQMS. In addition to this, a Data Inspection Procedure for the physical validation of product attributes is also included on the Framework.
How should the Data Quality Framework be used?
The Data Quality Framework is a flexible document that can be used for multiple purposes:
- it can be used to identify internal improvement opportunities
- to define processes
- to implement a data quality system, as a guide to perform efficient and reliable product/data audits.
In that sense, the usage of the Framework is dependent on the goals of each organisation.
In order to provide the user community with clear guidelines for the utilisation of the Framework within each one of these different scenarios, a document called the 'Data Quality Framework Implementation Guides' has been created. Please contact Alan Gormley for a copy and information on implementing Data Quality practices within your organisation.
The GS1 Global website hosts a comprehensive FAQ on the Data Quality Framework.