TDWI The Data Warehousing Institute

Prerequisite: None

One-Day Course

Knowing what happens with your data is only the beginning of data quality management. Understanding why things happen is a fundamental management skill and an essential skill for anyone who is challenged to manage data and information quality. Understanding why things go wrong is the key to knowing what to do. But cause-and-effect relationships are elusive. Real causes are often difficult to find, so we settle for easy answers, which leads to fixing symptoms instead of solving real problems. Root cause analysis is the alternative to easy but ineffective answers. Looking beyond the apparent and obvious to find real causes brings insight and sows the seeds of foresight—the tools to resolve today’s quality issues and prevent tomorrow’s problems.

Through this course you will see how data profiling is applied to understand the what of your data, and root cause analysis is used to understand the why of data conditions. Learn to apply data profiling, linear thinking, lateral thinking, systems thinking, and critical thinking—independently and in combination—to get to the core of even the most vexing data quality problems.

You will learn how to

• Use data profiling techniques to detect data quality issues
• Perform causal analysis to identify root causes of data quality problems
• Perform fast and light causal analysis using the “five whys” technique
• Explore linear cause-and-effect chains with fishbone diagramming
• Describe complex cause-effect networks with causal loop models
• Challenge and refine linear and loop models with lateral and critical thinking techniques
• Apply root cause analysis to improve the quality of data and data management processes

Geared to

• Data quality professionals and practitioners; quality management and quality improvement professionals; business analysts and business analytics professionals; anyone responsible for managing data, information, people, process, or technology