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Meta Data & Knowledge Management: Independent Data Marts: Stranded on Islands of Data, Part 3

by David Marco

This column is the third and concluding portion of a three-part series on migrating from independent data marts. In parts one and two, we examined the characteristics of independent data marts, the flaws in their architecture, the reasons why they exist, approaches for migration, initial planning and how to identify a migration path. In this month's column, I will present a case study illustrating how a corporation can migrate from independent data marts to an architected data warehousing solution.

Putting the Concepts into Motion

This case study illustrates the iterative approach to independent data mart migration, as most companies that have independent data marts typically have a pervasive and complex situation.


The Surefire Electronics Company is a Fortune 500 consumer electronics firm. Surefire Electronics recently acquired a smaller company (Small Guys Electronics) that has a single marketing data mart about which little is known. In addition, Surefire Electronics is standardizing on a new order-entry system within five years, and existing batch windows for the legacy systems have reached their limit. Surefire Electronics' management team is stable, well organized and fully supports the migration effort. Figure 1 lists Surefire Electronics' specific data warehousing details and Figure 2 shows their independent data mart architecture.

Figure 1: Example Background

Figure 2: Independent Data Mart Architecture

By viewing the data within each of the data marts, it is evident that the marketing and finance data marts share two common data sources (old and new order entry systems). In addition, the marketing data mart has a strong end-user community that will be highly supportive of the migration effort. With a little bit of help from our executive management, both the marketing and finance data marts' business users agreed to freeze their additional functionality requests for Phase One of the migration.

During this phase, we avoided migrating the quality control and the Small Guys' marketing data marts. This decision was made because of the lack of support in the quality control mart and all the "unknowns" of the Small Guys' marketing mart. Figure 3 illustrates the Phase One data warehousing architecture.

Figure 3: Phase One Data Warehousing Architecture

Phase Two Migration

The development effort that occurred in Phase One should illustrate the value of having an enterprise data warehouse. The data warehousing team can now capture the amount of data that no longer requires storage because detailed data is stored in one spot, and the number of technical processes has been reduced. With this information in hand, the data warehousing team embarked on Phase Two.

During this phase, the logistical system's data was brought into the data warehouse, and the quality control data mart is now being sourced directly from the enterprise data warehouse. In addition, during this phase, the marketing and finance teams' change requests that were frozen during Phase One implementation were developed. Lastly, a new dependent accounting data mart is now being sourced from the data warehouse (see Figure 4).

Figure 4: Phase Two Data Warehousing Architecture

Phase Three Migration

In this phase, we examined the functions and features of the Small Guys Electronics' data mart. During this examination, we found that the end users' data needs were very similar to those needs of the current marketing data mart. Therefore, Phase Three consists of merging the functionality in the former Small Guys Electronics' marketing data mart into the existing dependent marketing data mart and the addition of a new ceo data mart. See Figure 5.

Figure 5: Phase Three Data Warehousing Architecture

It is important to understand that the process for migrating from an independent data mart architecture is a costly proposition that will only get more expensive and difficult as time goes on. Remember, as with any disease, the earlier it is detected and treatment begins, the sooner the patient will become healthy. However, if treatment is delayed, the patient's condition will worsen and eventually become terminal.

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

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