Knowledge

ISO 8000-1:2022 is an international standard that governs Data Quality Management, ensuring that data used within organizational systems is accurate, reliable, and trustworthy. This standard provides structured guidance for organizations in data management, thereby improving operational efficiency, reducing the risk of errors, and ensuring compliance with data regulations. 

Key Principles of ISO 8000-1 

ISO 8000-1:2022 establishes several key principles for managing data quality, including: 

• Data Identification and Documentation: Organizations must be able to identify the data used in their operational processes and document its characteristics and attributes. 

• Data Accuracy: Data must be accurate and relevant for its intended purpose. 

• Data Interoperability: Data should be easily usable and exchangeable between different systems and organizations. 

• Data Security: Organizations must ensure that data is protected from potential security and privacy threats. 

• Data Availability: Data must be available in a timely manner when needed. 

• Data Measurability: Data must be measurable and assessable to ensure its quality. 

ISO 8000-1:2022 Framework 

1. Data Roles in ISO 8000-1:2022

ISO 8000-1:2022 categorizes data into several main types: 

• Master Data Master data is core data that defines essential business elements within an organization. It serves as a single source of truth to support key business processes and forms the foundation for consistency and interoperability within the organization. Examples include customer data, product data, supplier data, location data, and employee data. ISO 8000-1:2022 emphasizes that organizations should have robust Master Data Management (MDM) before further implementation. Master data must meet quality criteria such as accuracy, completeness, and consistency. 

• Reference Data Reference data consists of standardized data that provides context or classification for other data. It supports interoperability and data exchange across systems or organizations and helps align terminology and data classification for uniformity. Examples include postal codes, telephone area codes, currencies, units of measurement, and international standards. ISO 8000-1:2022 stresses that reference data should be documented with clear metadata to ensure consistent use, and it encourages the use of open-standard based reference data to enhance reliability in data integration. 

• Transactional Data Transactional data is generated from day-to-day business activities. It provides a record of activities that support operational processes and is used for data-driven analysis and decision-making. Examples include sales invoices, purchase orders, and financial transaction reports. ISO 8000-1:2022 emphasizes that the quality of transactional data is highly dependent on the quality of master data and reference data, ensuring that transactional data is well-structured and has clear traceability. 

• Metadata Metadata is data about data, describing its attributes, structure, and context. It enhances data understanding and interoperability and ensures transparency in data management. Examples include data element names, data types, formats, and relationships between data. ISO 8000-1:2022 highlights that metadata is a key element in this standard for supporting data quality documentation and validation, requiring the use of standardized metadata as the basis for data quality management. 

• Derived Data Derived data is data generated from the manipulation or combination of other data. It adds value through data processing and supports strategic decision-making. Examples include analytical reports, data-driven predictions, and Key Performance Indicators (KPIs). ISO 8000-1:2022 emphasizes that derived data must be based on quality data to produce accurate and reliable outputs. 

• Historical Data Historical data represents past information. It supports trend analysis and historical reporting and is useful for regulatory compliance and audits. Examples include transaction history, annual sales data, and patient medical records. ISO 8000-1:2022 stresses that historical data must be properly stored and managed to ensure accessibility and authenticity. 

The roles of data in ISO 8000-1 encompass various data types that work together to ensure data integrity, consistency, and interoperability within an organization. Master data and reference data form the core that supports transactional data, metadata, derived data, and historical data. Implementing ISO 8000-1 requires a comprehensive approach to ensure each data type is managed in accordance with data quality principles. 

2. Data Architecture in ISO 8000-1:2022

This framework encompasses how data is organized, stored, accessed, and managed within an organization. This architecture is designed to ensure that the data used meets quality standards, is accessible, and supports operational and business decision-making. Key Components of Data Architecture: 

• Data Structure Identifies how data is organized, including its format, data types, and relationships between data elements. Example: A database designed with entities such as “Customers,” “Products,” and “Transactions.” 

• Metadata Management Metadata supports transparency and understanding of data by explaining attributes and relationships between data elements. 

• Data Processes and Flow Defines how data moves throughout systems, from input to processing and output. 

• Data Security and Access Regulates access rights and controls to ensure data security, including protection against breaches or misuse. 

Furthermore, a Data Dictionary is also an important part of data architecture, serving as official documentation regarding the data within a system. A data dictionary is a structured collection of information that records: 

• The definition of each data element. 

• Data structure (data type, length, format). 

• Data attributes (relationships with other elements, default values, etc.). 

A data dictionary typically includes the following information: 

• Data Element Name: A unique name for each element. 

• Description: An explanation of the data element’s purpose. 

• Data Type: Such as string, integer, or date. 

• Format: Specifications on how the data is presented (e.g., “YYYY-MM-DD” for dates). 

• Allowed Values: If any, such as a list of codes or numerical constraints. 

• Data Relationships: Explains relationships with other data elements. 

Relevance of Data Architecture and Data Dictionary to ISO 8000-1 

ISO 8000-1 emphasizes the importance of good documentation, including a data dictionary, as part of quality data management. A data dictionary helps organizations achieve transparency, consistency, and traceability in data usage. The elements within a data dictionary support data validation processes, interoperability, and improved data-driven decision-making. A sound data architecture, supported by a data dictionary, enables organizations to ensure that data is reliable, standard-compliant, and supports business objectives. 

3. Scope of ISO 8000-1 Implementation

The scope of implementation begins with determining the types of data that are prioritized for management. This includes identifying data critical to the operational or strategic success of the organization. Examples of Implementation Scope Based on Data Type: 

• Retail Companies: Focus on product data, including product catalogs, pricing, stock, and suppliers. The objective is to improve inventory management efficiency and customer experience. 

• Accounting Firms: Focus on financial records, such as transaction reports, ledgers, and audit data. The objective is to ensure compliance with financial regulations and enhance reporting accuracy. 

• Government Organizations: Focus on population data (e.g., demographic data from Dukcapil) or tax data. The objective is to improve public services and transparency. 

Determining the scope of ISO 8000-1 implementation is highly flexible and adapted to the specific needs of the organization. Identifying the data to be managed is the crucial first step to ensure that data quality management efforts focus on the elements that provide the greatest impact for the business. With this approach, organizations can maximize the benefits of implementing the ISO 8000-1 standard. 

4. Data Owning Industries

ISO 8000-1 is designed to be flexible and adaptable to the specific needs of various industries. To this end, the standard has extensions that support data management according to the characteristics and requirements of particular industries. Here is an explanation of the standard’s application based on industry type: 

• Manufacturing Industry The manufacturing industry requires highly precise data management to ensure efficient and accurate supply chains. Extension Used: ISO 8000-115 (Smart Prefix), which functionally helps in the unique identification of components, products, or items within the supply chain. Example Implementation: Identifying components such as bolts, nuts, or electronic modules with unique codes that can be recognized by all parties in the supply chain. 

• Banking Industry Banking focuses on managing transactional data, customer data, and digital format-based documents, especially XML (Extensible Markup Language). Extension Used: ISO 22745, which functionally supports efficient and consistent XML-based data exchange. Example Implementation: Interbank transaction data using standardized XML format to ensure smooth information exchange. 

• Legal Industry In a legal context, data is often used for documentation, regulatory compliance, and legal document storage. Extension Used: ISO 8000-116, which functionally provides standards for managing data relevant to legal or regulatory contexts. Example Implementation: Management of contracts or agreements accompanied by standardized metadata such as creation date, involved parties, and reference numbers. 

Data-owning industries have different needs, and ISO 8000-1 provides flexibility through specialized extensions, such as ISO 8000-115 for manufacturing, ISO 22745 for banking, and ISO 8000-116 for legal. By applying these extensions, organizations can ensure that their data management aligns with specific industry needs, supports interoperability, and improves overall data quality. 

5. Quality Identifier (QI)

A Quality Identifier (QI) is a key element in ISO 8000-1 aimed at providing unique, accurate, and reliable identification for data, as well as ensuring the traceability of the data’s source or owner. For example: 

• Banking Data: A key identifier such as BRI123456789 can be used to indicate that the data belongs to Bank BRI. 

• Population Data: NIK (Nomor Induk Kependudukan) data from Dukcapil is equipped with a unique key identifier for each individual. 

• Health Data: Data belonging to BPJS (Indonesia’s National Health Insurance) is given a unique identifier, e.g., BPJS-5678-2025, to differentiate it from other healthcare providers. 

A Quality Identifier is a crucial element in managing quality data. By providing unique and clear identification for each data element, QI supports accountability, transparency, and efficiency in data management and exchange. Its implementation allows organizations to ensure that the data they use is trustworthy, free from duplication, and easily integrated into broader systems. 

Benefits of Implementing ISO 8000-1:2022 

Implementing ISO 8000-1:2022 provides various benefits for organizations, including: 

1. Improved Data Quality ISO 8000-1:2022 helps organizations ensure that the data used in business processes is accurate, complete, consistent, and reliable. Improved data quality contributes to more precise and faster decisions. 
2. Operational Efficiency With well-managed data, organizations can reduce the time spent searching for, cleaning, and correcting inaccurate data. It also helps reduce duplication and promotes more efficient workflows. 
3. Reduced Business Risk Poor data can lead to operational and financial errors. With better data quality, organizations can reduce potential risks related to data errors, for instance, in financial reports or regulations. Implementing ISO 8000-1:2022 helps minimize errors in data that can affect business decisions. 
4. Increased Customer Trust Customers tend to trust organizations more that demonstrate a commitment to quality data management and transparency. Implementing ISO 8000-1:2022 can serve as proof that the organization cares about the quality and integrity of the data it manages. 
5. Supports Digital Transformation Good data management is the foundation of many digital transformation initiatives. ISO 8000-1:2022 facilitates the use of new technologies, such as big data and analytics, by ensuring the quality of managed data. 

By implementing the ISO 8000-1:2022 standard, organizations can improve overall data management, which can support better decision-making, reduce operational costs, and enhance customer satisfaction. 

Written by Syifa Aulia Sari – Team Leader IT GRC Robere & Associates (Indonesia), 2025 

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