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

CBIP

Prerequisite: None

Gian Di Loreto

Ph.D.

This course gives an overview of best practices for measuring data quality and for data cleansing based on real-world experience. Attacking the problem from both theoretical and practical perspectives, students will enjoy a clear lecture focused on modern data quality assessment and cleansing techniques followed by examples of data quality problems and solutions provided using some of the front runners in the data quality software solution space (currently including Trillium, DataFlux, Talend, and Informatica). Taking data quality from theory to practice, the course allows students to tackle their data quality problems back at the office with a clear starting point and path, and finish using the methodology and examples based on instruction we provide.

You will learn

• Current best practice techniques used by top practitioners in data quality and cleansing
• How to definitively measure data quality in a format that can be used as a standard metric
• How to navigate through common data quality roadblocks
• How to make the case for data quality assessment and full data cleansing exercises both inside and outside your company
• How to leverage Sarbanes-Oxley legislation to motivate your data quality initiatives
• To what extent current commercially available tools can help with your data quality initiatives (including Trillium, DataFlux, Talend, and Informatica).

Geared to

• Current or future data quality practitioners in the trenches of a data quality or cleansing initiative; managers of data quality groups; those who wish to evaluate some of the current data quality tools in the marketplace