October 1, 2009
In most organizations today, data and other information aremanaged in isolated silos by independent teams using assorteddata management tools for data quality, integration, governance,meta- and master data management (MDM), content management,and so on. From a technology viewpoint, the lack of coordinationamong data management disciplines leads to redundant teamstaffing and limited developer productivity. Even worse, competingdata management solutions can inhibit data’s quality, consistency,standards, scalability, architecture, and so on. From a businessviewpoint, data-driven business initiatives suffer (including BI,CRM, and business operations) as a result of poor data quality andincomplete information, inconsistent data definitions, noncompliantdata, and uncontrolled data usage.
Forward-looking organizations are solving these technology and business problems by adopting enterprise data management (EDM). Download this TDWI Checklist Report to learn more about this best practice for unifying diverse data management disciplines.