Over the past year, I've read a couple of articles that described the task of meta data management as "meta data misery," "a necessary evil" and "meta data morass." In these articles, the authors discuss meta data management as if it is some horrible ill that companies are forced at gunpoint to endure. I am quite surprised by this viewpoint, as implementing a managed meta data environment (MME) isn't any more difficult than building any very large, highly complex enterprise spanning application. For example, the success rates for MMEs are significantly higher than those of customer relationship management (CRM) applications, which fail approximately 90 percent of the time. Moreover, while enterprise MMEs are expensive projects, their costs pale in comparison to typical enterprise level CRM, enterprise resource planning (ERP) and/or data warehousing initiatives. It is these same individuals that state that corporate executives don't care about meta data management. A recent survey asked CIOs about the goals of innovation and the technologies that they believe will deliver innovation. I would like to examine the results of this survey and ask the question: Should your CIO care about meta data management?
What Do CIOs Care About?
Before we can decide if the CIO should care about meta data management, we need to first understand what CIOs do care about. Figure 1 shows the results of a survey of CIOs that marked each of the technologies that they believe would provide the greatest levels of innovation.
We are going to walk through these key innovative technologies and see where and if meta data management plays any role.
Figure 1: Key Technologies for Innovation1
Redesigning or Rationalizing IT Architecture: The need to redesign/rationalize IT architecture was by far the survey leader with 73 percent of CIOs citing this as an innovative technology. It may be surprising to some to see rationalizing IT architecture as being the top innovative technology choice for CIOs; however, this is a distinct trend that has emerged from the glut of redundant applications and needlessly interdependent processes that have handcuffed most large organizations' IT departments.2
Because redesigning IT architecture is not a specific technology, it is important to understand what technology best enables an organization to redesign your IT architecture. Before we can address this question, we need to have a clear understanding of the key components of your IT architecture. Key architectural components include:
- Data Attributes
- Manual Processes
Before it is possible to redesign these components, one must understand (the following is a partial list):
- What components exist.
- Where they exist.
- What they are used for.
- Who uses them.
- Data stewardship.
- What the data means.
- How each component interacts with each other component.
Those of you who are meta data practitioners realize that all of this information is really meta data. In fact, every successful enterprise architecture team that I have ever worked or spoken with has come to the realization that they are a meta data management team. The reason is that a managed meta data environment provides the key functionality for redesigning an organization's IT architecture. In fact, it would be impossible for a Global 2000 company or any substantial government organization to attempt this without meta data management. Just imagine if the average company attempted to manually track the 500,000 to 3 million individual data attributes in your IT architecture. Now think of the effort it would take to manage the 30 million or more data lineage relationships between these data attributes! Regardless of how intelligent a person or group of persons may be, it is impossible to manage this meta data without the assistance of an application. The application that gathers, retains and disseminates this information (meta data) is the managed meta data environment.
Data Access/Warehousing: Fifty-five percent of CIOs believe that data warehousing and access to data technologies can provide critical innovation to their organization. Many companies' first generation data warehouses focused on integrating data from their source systems and presenting that data to their end users. Typically, these "data warehouses" had limited data volumes and more resembled a data mart rather than a "true" data warehouse. As companies become more sophisticated, their data warehouses entered into their second generation. This iteration tended to evolve their data warehouses into large, multiterabyte enterprise applications. Of course, the demands of the business have continued to push data warehousing forward into the "active" world. We see that companies no longer want to supply chain information that is updated as of last night. Now they want the data to be as current as is possible.
It is common for end users to complain that they have lots of data "thrown" at them but they don't understand the data and they don't have "actionable" information. By "actionable," I mean information that answers whatever question the end user needs answered so that they can do their job better, faster and more effectively.
Anyone who has ever worked substantially in the data warehousing field understands that meta data management is critical for evolving your data warehouse through its different iterations. In addition, business meta data that is presented to the end users is an absolute necessity in transforming data into actionable information.
Next month, I will continue to walk through the key innovations that CIOs want and the vital role that meta data management plays.
- CIO Magazine, April 1, 2005 (respondents checked all that applied).
- For a more detailed discussion on this topic, see Chapter 1: Facing Corporate Challenges with an MME, Universal Meta Data Models, by David Marco and Michael Jennings, John Wiley & Sons 2004.
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