ISO/IEC 5259 — Data quality for analytics and ML 


ISO/IEC 5259 is an international standard that provides guidelines for data governance, data quality assessment, measurement, and improvement for both training and operation. This standard comes in 6 parts, where only four have been already passed to the Committee Draft stage by ISO. This course will cover these four parts. Our course is structured based on a top-down approach allowing trainees to book one or multiple days tailored to their needs. However, the exam given on the 4th day requires that all training days (1-to-3) have been followed by the trainee.


Day 1: 


    • Data quality concepts for analytics and ML
    • Data quality model for analytics and ML
    • Data quality characteristics and quality measures
    • Data quality reporting


Day 2: 


    • Data requirements for conformance
    • Overall data quality management
    • Data quality management lifecycle-specific recommendations and requirements
    • Horizontal processes
    • Data quality management in supply chain
    • Methods to improve data quality
    • Management of data processing tools
    • Management of data quality dependencies

Day 3:


    • Data quality process framework
    • Data labeling methods and processes
    • Roles and participants in data management framework
    • Data quality process for semi-supervised ML
    • Data quality process for reinforcement learning
    • Data quality process for analytics
    •  ½ day exam covering all the course topics.

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