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Meta Data Themes - Part 2: Advanced Themes

by Robert S. Seiner

Part 1  |  Part 2


In the first part of this article, I offered information about basic meta data themes that could be used as an easy-to-understand starting point for meta data management. I wrote about several types of the projects that are common in large corporations. By looking at similarities in the projects, we found that there are several basic themes that persist across projects. Those basic themes included the need for data administration, database administration, and data movement meta data. The article broke down each of these themes into a limited number of components (meta data entities) that provided a basic starting point for identifying the "right" meta data to manage.

The concept of advanced meta data themes discussed in this article takes the concept of basics themes to the next level. Advanced themes expand beyond the entities discussed earlier to include components of meta data that relate to data access, data quality, and data accountability.

The following sections break down the three basic meta data themes into their quality, access, and accountability components and offer considerations for the types of meta data to manage beyond the basics:

Data Administration Meta Data

      • Data quality components
          • Business rules relating logical entities: Information from the data models that identify entity relationships and business rules of how the entities interact with other entities educate end-users on related data that may be available and how it can be understood and used.
          • Acceptable values and domain definitions, compliance percentage, missing rules: Information comparing domains (sets of legal values) defined in data models to actual data occurrences. Data users will be interested in how the actual values compare to how they are defined and the actions that are taken if the data is missing or outside of the domain.
          • Data rationalization and aliases; how data is defined similarly across the enterprise: Information about how data is mapped from one data store or application to another. This does not necessarily involve data movement since the same data can be defined independently (we know) in several systems. Information about the use of aliases including logical and physical aliases, potential aliases, and straight move type aliases.
          • Data standards / policies / procedures / restrictions / landmines: Information about data standards that include information policies, restriction on use of data and information, known problems that have not been corrected and that can easily be misinterpreted.
          • Business policies affecting data capture and data reporting: Changes in corporate policies that directly alter the way data is captured or interpreted.
      • Data access components
          • Mapping between logical data models and physical databases: Information about the relationships between the logical data models and the physical databases. Mappings are often created in the modeling tools during forward and reverse engineering processes and are accurate to the degree that databases and models are kept in synch. This information helps the end-user approach the physical data through its logical description.
          • Descriptions of subject areas, entities, attributes, legal values and changes over time: Information about how the data is organized and defined. Information about changes to the data subject areas, business entities and attributes, legal values and the meaning of those values.
          • Translation of business names to physical names and vice-versa; glossary: Information about abbreviated data names and tokens words that will enable power users to better understand the physical data. Also information about how to identify the physical data from business data names. Glossary components, their meaning, and their usage.
          • Accountability components: Contact information about the individuals responsible for enterprise / project data models, data and data warehouse architects, building and supporting the decision support database, data and those responsible for business policy and communications.

Questions that advanced data administration meta data can answer:

— How have business changes impacted the data? What affect does this have on data interpretation?

— What confidence can I have in query results & reports knowing that there are data quality issues?

— How can I get answers if all I know are the questions?

— Where in the company is do we capture this type of data and how does it differ across applications?

— Who do I contact if I have a question about data administration issues?

Database Administration Meta Data

      • Data quality components
          • Balancing Row Information: Information about number of result totals or rows expected and actual numbers. May indicate problems with selections, extracts, transformation and / or movement.
          • Table counts and growth information: Information about table growth rates; Information that is regularly required for capacity planning.
          • Coordination of process: Information that improves communications between DAs and DBAs to provide the capability of keeping the physical database in synch with the data models. This includes creation / alter / drop actions that would call for forward and reverse engineering actions.
      • Data access components
          • Data usage and activity: Information about the data that is being accessed and how often. Also, information about data that is not being accessed.
      • Data access activity and performance
          • Information about the performance of queries; normal processing time for queries; best times to execute, preferred indexes that improve performance.
      • Data refresh and timing schedules
          • Information about data refresh schedules and periods, when the last refresh took place and the level of completeness.
      • Accountability components
          • Contact information about the DBAs responsible for database creation, maintenance, performance. Help desk information available when or if the database goes down.

Questions that advanced DBA meta data can answer:

— What data is being used? By whom? When is it available or "busy"?

— How will I know if I am receiving all of the information that I requested?

— Are the business descriptions in synch with the databases?

— When was the last time this data was updated and did that process end successful?

— Who do I contact if I have a database problem or question?

Data Movement Meta Data

      • Data quality components
          • Data value determination and rules: Information about how the value of the data was determined including the field names from the operational data, what was done when data was missing or contained an illegal value, and the confidence level for the data.
        • Data creation source
          • Information about the location of the person, terminal, date associated with the creation of the data. This information could be used to identify data origin and system problems.
      • Data access components
          • Movement timing: Information about when the data movement takes place and how that will affect source and target database outages or restricted periods for access
          • Staging information and verification access: Information about how data is staged along an information pipeline and how that information can be accessed and verified along its route.
      • Accountability components
          • Contact information for the individual who architected the data movement and rules. Information about the "owner" of the source data. Information about the "owners" of the data movement tools and / or programs developed to select, extract, transform and move data.

Questions that advanced data movement meta data can answer:

— What massaging was done to the data as it was moved? Has it always been done that way?

— What did this data look like before it got to me and at what point in the pipeline did it change?

— Where did this data originate and who was responsible for the data creation / integration?

— Will movement activities affect my ability to report on it timely and accurately, on my schedule?

— Who do I contact if I have a problem or question about how data was moved, transformed?

In these two articles, I have discussed the concept of meta data themes from the basics to the advanced. By breaking data administration, database administration, and data movement meta data into quality, access, and accountability components, I have given novice and beginning meta data managers a starting point for identifying the meta data that can be made available in the typical large company.

Often companies have a difficult time justifying the management of the basic meta data. There are not many companies that have the ability to manage all of the meta data described in this article. If prospective meta data managers use the information and questions provided in these articles as a starting point for meta data needs assessment and requirements definitions, they will find that most of the meta data that they define as "necessary to manage" will fit into a data administration, database administration, or data movement category (or theme). It is also quite likely that the meta data will be tightly related to the improvement of data quality, data access, or accountability for data resource.

Copyright © The Data Administration Newsletter 2002 - Robert S. Seiner


Robert (Bob) S. Seiner is recognized as the publisher of The Data Administration Newsletter (, an award winning electronic publication that focuses on sharing information about data, information, content and knowledge management disciplines. Mr. Seiner speaks often at major conferences and user group meetings across the U.S. He can be reached at the newsletter at or 412-220-9643 (fax 9644).

Mr. Seiner is the owner and principal of KIK Consulting Services, a company that focuses on Consultative Mentoring or simply stated ... teaching company's employees how to better manage and leverage their data, information, content, and knowledge assets. Mr. Seiner's firm focuses on data governance/stewardship, meta-data management, business intelligence and knowledge management. KIK has developed a 4-Step Method© for Consultative Mentoring that involves customizing industry best practices to work in your environment.

For more information about Mr. Seiner, KIK Consulting Services and The Data Administration Newsletter (, please visit and

Contributors : Robert S. Seiner
Last modified 2006-01-04 01:03 PM
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