Master Data Management

Taxonomy and metadata management are critical to ensuring enterprise data quality.  Robust data quality is a prerequisite for creating trusted and optimized data applications, both for internal tasks (such as business intelligence) and customer-facing applications (such as e-commerce websites).  In this session, we look at approaches for cleansing, harmonizing and creating data structures for data that is below required quality thresholds.  This webinar uses as an example product data quality, but has broad applicability to master data management (MDM) in general.

Seth Earley provides an industry perspective focusing on the business need for taxonomy and metadata management to MDM.

Rennie Walker discusses a recent large-scale product data quality project for a major retailer.  This segment of the webinar offers insights into methodology, approaches to project design, governance and lessons learned.  In addition, Rennie addresses the capabilities and functionalities of data quality tools, using Oracle's PDQ (Product Data Quality) suite as an example.