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.
Agenda
Day 1:
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- 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:
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- 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:
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- 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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