Keeping data consistent across business functions such as marketing and customer support is essential for the vitality of today's organizations. But when companies need to integrate data between applications, the consistency of data, or data quality, becomes an issue. Basic problems such as null fields, duplicate records, syntax problems, range problems and more, impact data quality and with multiple application sources and master data management, it becomes a complex and expensive problem to solve.
In this video <http://bit.ly/qY0RFx>, Michael Zuckerman, chief marketing officer for Queplix™ Corp <http://www.queplix.com/>., outlines a template for data integration that involves automating data quality processes. This step by step template discusses the essentials of data quality - measurement and review, reporting and remediation, data governance, and data normalization and alignment, whether integrating two data sources or many. A highly automated approach <http://www.queplix.com/products/architecture.html> delivers a faster, easier method to maintaining data quality, reducing risk, and improved results.
To learn more, see http://bit.ly/qY0RFx.
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