Chapter Ten. Step 10: Meta Data Repository Design


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Chapter Overview

This chapter covers the following topics:

  • Things to consider when designing a meta data repository or when evaluating meta data repository vendor products

  • How the shortcomings of early meta data initiatives contributed to failures to effectively manage meta data

  • The multitude of meta data sources we now have to manage in a BI decision-support environment

  • The advantages and disadvantages of three different types of implementation strategies: a centralized meta data repository, either built or licensed (bought); a decentralized meta data repository; and a distributed meta data solution enabled through the use of Extensible Markup Language (XML) tags

  • The advantages and disadvantages of two different types of meta data repository designs: an entity-relationship (E-R) design and an object-oriented (OO) design

  • Detailed examples of the product and vendor evaluation process

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

  • The risks of not performing Step 10

Things to Consider

Existing Meta Data Repository

Do we already have a meta data repository?

Do we have to expand it? Do we have to add more meta data components ? Or expand the functionality?

Who is keeping the meta data repository up-to-date?

Who is using it? How are they using it? What parts of the meta data repository are they using?

Do they like it? Are there any complaints?

If we do not have a meta data repository, how are we coping without one?

Why do we not have one? Lack of budget? Lack of resources? Lack of understanding?

Meta Data Repository Products

Are there meta data repository products that will satisfy our meta data requirements? Or do we have to build a meta data repository from scratch?

How many of our meta data requirements cannot be satisfied by the meta data repository products on the market? How important are those meta data requirements?

Can the meta data repository products be enhanced to meet those specific meta data requirements?

Which meta data repository products have import and export capabilities?

Interfaces

How will we automate the interfaces from the meta data repository to other tools that have their own meta data dictionaries, for example, computer-aided software engineering (CASE), extract/transform/load (ETL), and online analytical processing (OLAP) tools? Will we have to buy additional middleware?

Do the other tools from which we have to extract meta data have import and export capabilities? Are those tools XML-enabled?

How will we deliver the meta data to the business people? Through reports ? Through a help function? Through a Web interface?

Will it be hard for the business people to learn how to use the meta data repository interfaces? What training do we have to develop?

Staffing

Will we need more staff to install, enhance, and maintain a licensed meta data repository product?

Will we need more staff to design, build, and maintain our own custom-built meta data repository?

The term meta data is not new, and efforts to manage meta data are not new either. What is new is the increased awareness that meta data is an important extension to business information and that managing meta data is therefore mandatory. Another important recognition is that new tools and techniques for managing meta data are needed ”and are becoming available.



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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