This course is designed for individuals and teams responsible for or interested in maintaining data quality in their business processes, systems, or databases. This includes Data Analysts, Data Quality Analysts, Business Analysts, Data Designers/Modellers, Data Stewards, Business Process Modellers, and Application Developers. Additionally, it can also be highly beneficial for managers and project managers who oversee these teams and need to understand what's involved in data quality management. Finally, this course is also a valuable resource for data users, such as data scientists, whose work is often impacted by data quality.

In the modern digital age, data quality is paramount for any organisation to operate efficiently, satisfy customers, and achieve set goals. This course provides you with a solid foundation and practical skills to manage and improve the quality of your data. By adopting the Ten Steps methodology, you will be able to turn data quality challenges into actionable projects with clear objectives, connect data quality issues with business priorities, and showcase the value and impact of data quality using business impact techniques.

'Ten Steps to Quality Data' is a comprehensive 3-day live streaming course based on the second edition of Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information™ (Elsevier/Academic Press, 2021). It provides a practical approach to creating, improving, and managing the quality of data critical to any organisation's success. The course includes discussion, exercises (both individual and group), and a project, giving you the opportunity to apply what you've learned directly to your organisation's needs.

The course does not specify an examination as part of its completion criteria.

Upon successful completion of this course, you will receive a certificate of completion from IRM UK.

1. The Data and Information Quality Challenge - Understand the importance of data quality and the role of the Ten Steps™ methodology.
2. Key Concepts for Addressing Information Quality - Learn about the Framework for Information Quality (FIQ) and the relationship between Data Governance, Stewardship, and Data Quality.
3. Step-by-Step: The Ten Steps™ Process - Detailed overview of the Ten Steps with instructions, techniques, examples, and best practices. 
    - Step 1: Determine Business Needs and Approach
    - Step 2: Analyze Information Environment
    - Step 3: Assess Data Quality
    - Step 4: Assess Business Impact
    - Step 5: Identify Root Causes
    - Step 6: Develop Improvement Plans
    - Step 7: Prevent Future Data Errors
    - Step 8: Correct Current Data Errors
    - Step 9: Monitor Controls
    - Step 10: Communicate, Manage, and Engage People Throughout

By the end of the course, you'll have the necessary knowledge and tools to effectively manage and improve the quality of data in your organization.