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Meta Data Management & Enterprise Architecture:
Industry Specific MME Applications, Part 2

  Column published in DM Review Magazine
November 2005 Issue
 
  By David Marco

This article is adapted from the book Universal Meta Data Models by David Marco and Michael Jennings, John Wiley & Sons, 2004.

Last month I began this series on industry-specific managed meta data environment (MME) applications by walking through a banking example. This column addresses MME applications for the healthcare insurance and manufacturing industries.

Healthcare Insurance Industry Example

Healthcare insurance companies were early adopters of MME applications. Healthcare insurance companies must adhere to a number of regulations. For example, many healthcare companies insure their employees. While this makes sense, it creates a problem: an insurance company cannot view the individual claims made by its employees.

For example, imagine that an employee is receiving treatments and submitting valid insurance claims for a drug-related problem. If an unauthorized employee looks at the employee's claims, this would violate several privacy statutes and could create potentially serious legal exposure for the insurance company.
Discount Health Company (DHC) wants to make sure that there is no unauthorized access to sensitive company reports. DHC has implemented a fairly limited-scope MME that captures user IDs and user names for each report that users access. DHC then uses this MME to generate a report that shows the restricted queries, user IDs, user names and security privileges (see Figure 1).


Figure 1: Healthcare MME Report: Security Analysis

Notice that this report shows that several users are accessing the highly sensitive "DHC Employee Claims" query. In viewing these users, it is clear that "Larry Williams" does not have the correct security privileges to be accessing this query. In addition, Larry did not access this report only once; he has accessed it 22 times over the past month.

This is a situation that needs to be handled on multiple fronts. First, there is a gap in the IT department's security process. The IT department needs to revisit its client/role security access. Second, a conversation needs to take place with Mr. Williams to determine why he has accessed the employee claims report more than 20 times. Using an MME gives DHC an opportunity to catch this problem early, before other people obtain access via the gap in the security process, and it will help reduce the likelihood of Mr. Williams talking about what he has been viewing.

Manufacturing Industry Example

As the size of a manufacturing firm grows, the need for an MME also grows. For example, all major automobile manufacturers have some sort of MME initiatives in production or development (although some of these initiatives could be architected and designed better). Our application scenario will focus on an automotive manufacturer.

FirstRateMotors (FRM) is a major automobile manufacturer that has a full range of automobiles but specializes in sports/performance and sport utility vehicles (SUVs). Like any manufacturer, FRM schedules and runs national marketing campaigns to help promote vehicle sales. FRM has an MME that targets business meta data specifically to support a marketing campaign management data warehouse. This data warehouse contains many marketing reports, including auto sales by auto type and by marketing campaign (see Figure 2).


Figure 2: Manufacturing MME Report: Automotive Report

A report such as the one presented in Figure 2 is a critical tool for any vice president of marketing or marketing director to understand the effectiveness - or ineffectiveness - of his or her marketing campaigns. Such marketing decision-makers use this report to make strategic decisions about the campaigns that they want to run. The ability to "hotkey" (that is, right click and press F1) on a row of data and receive data quality statistics would have tremendous value. Figure 3 shows how an end user can bring up these statistics.


Figure 3: Automotive Report: Data Quality Statistics

Suppose that you are trying to make a strategic decision about your "0 down and 0% Interest" marketing campaign. As you look at the sales numbers, you can see that the technical meta data shows that 2.3% of the records were not loaded into the data warehouse. As a result, there is a skew percentage of 2.3% associated with this field. A senior decision-maker in the marketing department would want to know that the numbers are skewed and by how much.

In my next column, I will continue to walk through specific industry examples of how an MME can provide value to national defense and pharmaceutical organizations. 

...............................................................................

For more information on related topics visit the following related portals...
Enterprise Achitecture.

David Marco is an internationally recognized expert in the fields of enterprise architecture, data warehousing and business intelligence and is the world's foremost authority on meta data. He is the author of Universal Meta Data Models (Wiley, 2004) and Building and Managing the Meta Data Repository: A Full Life-Cycle Guide (Wiley, 2000). Marco has taught at the University of Chicago and DePaul University, and in 2004 he was selected to the prestigious Crain's Chicago Business "Top 40 Under 40."  He is the founder and president of Enterprise Warehousing Solutions, Inc., a GSA schedule and Chicago-headquartered strategic partner and systems integrator dedicated to providing companies and large government agencies with best-in-class business intelligence solutions using data warehousing and meta data repository technologies. He may be reached at (866) EWS-1100 or via e-mail at DMarco@EWSolutions.com.



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