Prerequisite: None
Data quality is one of the most vexing of information management problems. Every organization has data quality challenges, but few are able to define the scope or quantify the magnitude of problems. You simply can’t begin to improve data quality without first assessing data quality. Yet much of data quality theory fails to step up to the complexities of data in the real world.
In academics there are two kinds of scientists: experimental and theoretical. In information management, there are theorists and experimentalists. Experimentalists deal with deadlines, crashing servers, angry clients, and idiosyncratic software. Theorists describe an ideal environment rarely found in reality.
Come join an experimentalist and learn his pragmatic, real-world approach to data quality assessment. You’ll learn proven and repeatable techniques while using computers loaded with state-of-the-art data management software from leading vendors (currently offering Trillium, DataFlux, and Talend). You will learn the principles of data quality assessment, then immediately put them into action in a computer lab–based environment. The class is a travelling small business, with workstations, a network, and a server loaded with Oracle, SQL Server, scrambled data, and data quality tools.
You Will Learn:
- Modern data quality assessment techniques
- How to create business-based data quality rules
- How to make the case for and manage a data quality initiative
- How to implement and manage programmatic, business-based data quality rules
- What the vendors offer today with hands-on experience
Geared To:
- Anyone challenged to define the size and scope of data quality problems; data analysts and managers "in the trenches" of a current or upcoming data quality initiative; anyone considering an investment in data quality tools who needs an overview of vendor offerings
Attendance is limited to 45.