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immediate downloadReleased: 2024-07-08
BS ISO/IEC 5259-3:2024 Artificial intelligence. Data quality for analytics and machine learning (ML) Data quality management requirements and guidelines

BS ISO/IEC 5259-3:2024

Artificial intelligence. Data quality for analytics and machine learning (ML) Data quality management requirements and guidelines

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Standard number:BS ISO/IEC 5259-3:2024
Pages:38
Released:2024-07-08
ISBN:978 0 539 14983 8
Status:Standard
BS ISO/IEC 5259-3:2024 Artificial intelligence. Data quality for analytics and machine learning (ML) Data quality management requirements and guidelines

BS ISO/IEC 5259-3:2024 Artificial intelligence. Data quality for analytics and machine learning (ML) Data quality management requirements and guidelines

Standard number: BS ISO/IEC 5259-3:2024

Pages: 38

Released: 2024-07-08

ISBN: 978 0 539 14983 8

Name: Artificial intelligence. Data quality for analytics and machine learning (ML) Data quality management requirements and guidelines

Status: Standard

Overview

In the rapidly evolving world of Artificial Intelligence (AI) and Machine Learning (ML), the quality of data is paramount. The BS ISO/IEC 5259-3:2024 standard provides comprehensive guidelines and requirements for managing data quality specifically tailored for analytics and machine learning applications. This standard is an essential resource for organizations aiming to leverage AI and ML technologies effectively and responsibly.

Why Data Quality Matters

Data quality is the backbone of any successful AI or ML project. Poor data quality can lead to inaccurate models, biased outcomes, and ultimately, flawed decision-making. The BS ISO/IEC 5259-3:2024 standard addresses these challenges by offering a structured approach to data quality management, ensuring that your data is reliable, accurate, and fit for purpose.

Key Features

  • Comprehensive Guidelines: This standard provides detailed guidelines on how to manage data quality for AI and ML applications, covering all aspects from data collection to data processing and storage.
  • Best Practices: Learn the best practices for data quality management, including data validation, cleansing, and enrichment techniques.
  • Risk Management: Understand the risks associated with poor data quality and how to mitigate them effectively.
  • Compliance: Ensure your data management practices comply with international standards and regulations, enhancing your organization's credibility and trustworthiness.

Who Should Use This Standard?

This standard is designed for a wide range of professionals involved in AI and ML projects, including:

  • Data Scientists
  • Machine Learning Engineers
  • Data Analysts
  • IT Managers
  • Compliance Officers
  • Project Managers

Benefits of Implementing BS ISO/IEC 5259-3:2024

Implementing the BS ISO/IEC 5259-3:2024 standard can bring numerous benefits to your organization, such as:

  • Improved Data Quality: Ensure your data is accurate, complete, and reliable, leading to more effective AI and ML models.
  • Enhanced Decision-Making: High-quality data enables better insights and more informed decision-making.
  • Increased Efficiency: Streamline your data management processes, reducing time and resources spent on data cleaning and validation.
  • Regulatory Compliance: Stay compliant with international data management standards and regulations, avoiding potential legal issues.
  • Competitive Advantage: Leverage high-quality data to gain a competitive edge in your industry.

Structure of the Standard

The BS ISO/IEC 5259-3:2024 standard is structured to provide a clear and logical framework for data quality management. It includes the following sections:

  • Introduction: An overview of the importance of data quality in AI and ML applications.
  • Scope: Defines the scope of the standard and its applicability.
  • Normative References: Lists the documents and standards referenced in the standard.
  • Terms and Definitions: Provides definitions of key terms used in the standard.
  • Data Quality Management Requirements: Detailed requirements for managing data quality, including data governance, data quality assessment, and data quality improvement.
  • Guidelines: Practical guidelines for implementing the data quality management requirements.
  • Annexes: Additional information and examples to support the implementation of the standard.

Conclusion

The BS ISO/IEC 5259-3:2024 standard is an invaluable resource for any organization involved in AI and ML projects. By following the guidelines and requirements outlined in this standard, you can ensure that your data is of the highest quality, leading to more accurate models, better decision-making, and ultimately, greater success in your AI and ML initiatives.

Invest in the BS ISO/IEC 5259-3:2024 standard today and take the first step towards achieving excellence in data quality management for your AI and ML projects.

DESCRIPTION

BS ISO/IEC 5259-3:2024


This standard BS ISO/IEC 5259-3:2024 Artificial intelligence. Data quality for analytics and machine learning (ML) is classified in these ICS categories:
  • 01.040.35 Information technology. Office machines (Vocabularies)
  • 35.020 Information technology (IT) in general
  • 35.020 Information technology (IT) in general