Chapter Fourteen. Step 14: Meta Data Repository Development


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Chapter Overview

This chapter covers the following topics:

  • Things to consider about meta data repository development

  • The many potential sources of meta data and the difference between active and passive meta data repositories

  • The need to develop two types of meta data repository interface processes: a tool interface process and an access interface process

  • The four types of testing that apply to meta data repository development: unit testing, integration testing, regression testing, and acceptance testing

  • Six activities to perform before the meta data repository goes into production

  • How to organize a directory for the meta data repository

  • Brief descriptions of the activities involved in meta data repository development, the deliverables resulting from those activities, and the roles involved

  • The risks of not performing Step 14

Things to Consider

Meta Data Repository Product Support

What interfaces are required for the meta data repository product?

Will we need to contact the meta data repository vendor for assistance with writing these interfaces?

Do we expect any problems with extracting meta data from the tools that originate it (e.g., computer-aided software [CASE] tool, extract/transform/load [ETL] tool, or online analytical processing [OLAP] tool)? Do we know if other companies experienced any problems?

Will we need to contact the tool vendors and ask for their assistance?

Can we embellish the meta data reports that are provided with the meta data repository product?

Does the meta data repository product have a context-sensitive online help function?

Custom-Built Meta Data Repository

Is our meta data repository design flexible enough to be expanded in the future?

Do we need to build a meta data repository directory as part of the access interface for the business people and for the technicians?

Do we need to build a context-sensitive online help function for the meta data repository?

Do we need to write meta data reports? How will we distribute them? On paper? On the intranet?

Will meta data be integrated with the queries and reports of the BI application? What type of process do we have to build to support that?

How can we ensure that the meta data in the meta data repository does not get out of synch with the meta data in the other tools and the database management system (DBMS)?

Staffing

How much can we modularize the coding and testing? Do we have enough developers and testers to speed up the development effort?

Will the same developers work on the meta data repository online help function? Or can we develop the help function in parallel?

Will we have full-time or part-time support from the database administrator? Will the same database administrator support the BI target databases?

Who will continue to maintain the meta data repository? Do we have a full-time meta data administrator? Is one person enough?

Are there any special training needs we have to consider? For the developers? For the business people?

Preparation for Production

Will the production meta data repository be installed on a dedicated production server? Who will install and test the server?

Do we need to set up any regularly scheduled meta data repository programs on the job scheduler? Will the operations staff run and monitor them?

Do we need to write operating procedures for the operations staff?

Do we need to write a reference guide for the help desk staff and for the business people?

To navigate through the BI decision-support environment more efficiently , business people must have access to a meta data repository. There are only two options: license (buy) a meta data repository or build one. Once a meta data repository is implemented, it has to be maintained and expanded over time. It also has to be populated and updated during each ETL process cycle with load statistics, reconciliation totals, data reliability metrics, data rejection counts, and the reasons for the data rejections.



Business Intelligence Roadmap
Business Intelligence Roadmap: The Complete Project Lifecycle for Decision-Support Applications
ISBN: 0201784203
EAN: 2147483647
Year: 2003
Pages: 202

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