The 17th Information Quality Conference 2005 Houston, TX, USA  September 19-23, 2005   IQ Product Sessions

Ensuring high data quality used to be considered just a problem, albeit a large problem, to be solved. However, businesses are starting to realize that good data quality has significant business potential on its own. Data that is accurate and fit for purpose enables stronger business performance and reduces costs in CRM, data warehousing, ERP, supply chain, and other enterprise systems. This is a critical shift. In the past businesses improved data quality to accomplish tasks such as correcting customer addresses for direct mailings, which can in fact save several hundred thousand dollars. Now, however, they see the larger data quality picture of more accurate data improving such processes as inventory management and business risk assessment, which can quickly return millions.

Savvy companies have been tackling Data Quality issues for years using a variety of homegrown and vendor technologies. Based on various forms of 'pattern recognition,' these systems have done well with name and address data and (semantically) simple data. However, standardizing, enriching and localizing more complex and variable data - such as the product master - has been a tougher nut to crack. Join this session to learn about semantic recognition - the new approach to making complex, variable data more usable for a variety of enterprise applications.

For years, organizations have tried an array of data integration efforts -EII, ETL, EAI, CDI - to create a "360-degree" view of the enterprise. However, these efforts often fail because they lack one basic requirement: a dedicated quality component. This session highlights how data quality solutions can build consistent, accurate and reliable information within data integration projects. Attendees will learn how data quality rules, enforced both in batch and real-time, can deliver a unified view of customers, products and suppliers.

This session will report early findings from DataDelta’s Single Customer View Accuracy Survey that accesses the “Single Customer View” accuracy from various Customer Data Integration (CDI) projects. This survey includes participating companies from a wide variety of industries and localities, and also includes a broad sampling of applications (such as marketing, Customer Relationship Management (CRM), corporate governance & compliance, fraud detection & prevention and more). This session will drill-down for multidimensional analysis of the preliminary data. Attendees will learn:

• What techniques & metrics are being used to measure match accuracy?
• How can those techniques & metrics be used for your own projects?
• How does your company compare with others in your industry & locality?
• What trends are emerging from analysis of the early survey results?
• What actionable information can be applied to improve your own operation?

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