Artificial intelligence - Data quality for analytics and machine learning (ML) - Part 1: Overview, terminology, and examples

What is ISO/IEC 5259-1?

ISO/IEC 5259-1 is the foundational part of the ISO/IEC 5259 series, focusing on data quality for analytics and machine learning (ML). This standard provides an overview, terminology, and illustrative examples to help organizations understand and apply the entire series effectively. It establishes the framework for assessing and enhancing data quality across different phases of the data life cycle, crucial for reliable analytics and ML outcomes.

Why is ISO/IEC 5259-1 important?

ISO/IEC 5259-1 is crucial because it addresses the foundational need for high data quality in an era dominated by data-driven decision-making. As data become the raw material for analytics and machine learning, ensuring their quality directly impacts the accuracy and reliability of analytical models and ML systems. This standard equips organizations with the necessary tools and methods to assess, manage, and improve data quality, ensuring that the data used are fit for their intended purpose. It provides a common language and set of practices that facilitate effective data quality management, crucial for achieving consistent and reliable analytics outcomes.

Benefits

- Improved rel