TDWI World Conference Las Vegas, NV February 12-17, 2012

Level: CBIP

Prerequisite: None

Dave Wells

CBIP

Data quality is one of the difficult challenges for nearly every business, IT organization, and BI program. The most common approach to data quality problems is reactive — a process of fixing problems when they are discovered and reported. But reactive data quality management quickly becomes a never-ending cycle of continuously fixing defects but rarely removing the causes. If you spend countless hours and dollars on data quality efforts but see little change in the quality of data, then it is time to take a different approach. It is time to proactively assess and systematically improve the quality of your data.

You Will Learn

• Why assessment is the critical first step in data quality management
• How to define the right criteria and the right processes for quality assessment
• How to collect and manage the metadata that describes data quality
• Techniques for data quality reporting and data quality scorecards
• How root cause analysis is applied to get beyond problems and symptoms
• How to develop and execute a plan for systematic data quality improvement
• Techniques to cleanse data and remove existing quality defects
• Techniques to improve processes and prevent future quality defects
• The human side of data quality — roles, responsibilities, and accountabilities

Geared To

• BI, MDM, and data governance program and project managers; BI, MDM, and data governance practitioners; data stewards; data warehouse designers and developers; data quality professionals