
AI data quality management bundle
Ensure high-quality data for analytics and machine learning with our comprehensive ISO/IEC 5259 standards bundle.
This bundle includes five essential components:
- ISO/IEC 5259-1:2024 - Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 1: Overview, terminology, and examples
- ISO/IEC 5259-2:2024 - Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 2: Data quality measures
- ISO/IEC 5259-3:2024 - Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 3: Data quality management requirements and guidelines
- ISO/IEC 5259-4:2024 - Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 4: Data quality process framework
- ISO/IEC 5259-5:2025 - Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 5: Data quality governance framework
AI data quality management bundle
AI data quality management bundle
pub200525
CHF
645
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Digital version (PDF), English
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Why choose this bundle?
This bundle provides a robust framework for managing data quality in the context of analytics and machine learning. Each component addresses a specific aspect of data quality management, from foundational concepts to governance frameworks.
- ISO/IEC 5259-1:2024 establishes the foundational concepts, terminology, and examples for understanding and applying data quality principles in analytics and ML
- ISO/IEC 5259-2:2024 specifies a data quality model, measures, and guidance on reporting data quality
- ISO/IEC 5259-3:2024 provides requirements and guidelines for establishing, implementing, maintaining, and improving data quality management
- ISO/IEC 5259-4:2024 outlines a data quality process framework, including guidance on data quality processes for various types of machine learning
- ISO/IEC 5259-5:2025 offers a data quality governance framework to enable organizations to direct and oversee data quality measures and management
Key benefits
- Comprehensive data quality management: Cover all aspects of data quality, from foundational concepts to governance
- Enhanced Analytics and ML Outcomes: Ensure high-quality data for reliable and accurate analytics and machine learning models
- Improved Organizational Capability: Build robust data quality management processes and frameworks
- Stakeholder Confidence: Demonstrate a structured approach to data quality, enhancing trust and credibility with stakeholders
Together, these standards ensure that your organization can effectively manage data quality, turning potential data challenges into strategic advantages.
Bundle content
- ISO/IEC 5259-1:2024Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 1: Overview, terminology, …
- ISO/IEC 5259-2:2024Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 2: Data quality …
- ISO/IEC 5259-3:2024Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 3: Data quality …
- ISO/IEC 5259-4:2024Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 4: Data quality …
- ISO/IEC 5259-5:2025Artificial intelligence — Data quality for analytics and machine learning (ML) — Part 5: Data quality …