Practical Data Quality

The course, illustrated with real case studies covers:

• What is Data Quality vs Data Quality Management and why does it matter?
• The DAMA dimensions of Data Quality, plus alternative views on Data Quality dimensions.
• The relationship between dimensions, measures, metrics along with their applicability.
• The benefits and impact of Data Quality.
• A reference model for Data Quality functions, capabilities, tools and reporting. What to look out for in a good reference model.
• The relationship between Data Quality, Data Governance and the other Information disciplines.
• Starting and sustaining a Data Quality initiative: steps for achieving Data Quality.
• Quality success, the activities, the structures required and the foundational activities.
• Data quality tooling; what can it do & what it can’t.
• Myths & traps about data quality & how to avoid them.