Many organizations are pursuing numerous data-oriented initiatives, such as Customer Integration, master data management, data warehousing and business intelligence, etc. These efforts all require a thorough understanding of the data needed to answer business questions, satisfy business needs and make it possible to pursue the goals of broader and deeper understanding of the data necessary for operations and decision-making. These needs all point to the reason many organizations are embarking on a data governance approach.

In the previous installment of this series, we saw some examples of the guiding principles organizations can use to realize the many advantages from embracing an Enterprise Information Management initiative. Those who embraced these key principles into their EIM initiative and understood the interdependency the framework components share were more likely to realize the immense business benefits. Some corporations still continue to struggle by approaching the framework components and the EIM initiative as projects, not as a cultural change.

In my last EIMInsight column I started walking through the key functions and features that my optimal meta data tool would have. In order to categorize these functions and features I am utilizing the six major components of a managed meta data environment (MME)

It seems like most of the focus surrounding enterprise solutions these days is on the technical strategy and specific tools. EIM Institute is a breath of fresh air as it puts the focus back on data management.

In last month’s post we talked about one of the foundations required for high information quality, accurate data. Many people think that is the sole prerequisite for achieving high information quality. Several people have written books discussing what you can do to increase the accuracy of the data that is used within your organization. These authors have identified practical and effective actions that can be used to increase data accuracy. But, as we have indicated before, this is typically not enough to guarantee highly accurate information within today’s complex and geographically dispersed organizations.