I had the opportunity to work with the Business Glossary feature of Sybase PowerDesigner. One of the organizations I work with already had licenses for Sybase PowerDesigner, so the Business Glossary feature came for “free.”

Here are the plus points associated with the Business Glossary feature of Sybase PowerDesigner:

• “Free” licenses – Organizations get an entry-level business glossary for free along with their licenses of Sybase PowerDesigner.
• Technical Metadata – Administrators can link business terms to the associated metadata from the data models within Sybase PowerDesigner.
• Quick Start – Data Governance teams can get up and running quickly with a nice user interface.
• Publishing – This is a very cool feature that allows the administrator to press a button and publish the glossary in HTML or PDF format. This document can be posted on SharePoint or some other portal. Data Governance teams can show quick results in a tangible format.
• Policies and Rules – The tool lets you create policies and rules, and then link those artifacts to the associated business terms. For example, create a term called “minors” and link to a rule that “minors must have guardians.”

On the other hand, I found some areas where the tool needed additional work:

• Stewardship – Ideally, a business glossary should allow administrators to assign terms and categories to data stewards. The tool has limited ability to support data stewards without paying for additional, expensive user licenses.
• Workflow – The tool does not support simple or complex workflows to allow multiple parties to participate in the creation of a term.
• Automatic creation of a code – I found this feature clunky. Sybase automatically creates a code for each business term. This code has to be one word. For example, the term “large customer” would be associated with a code called “large_customer.”
• Multiple definitions for the same term – Sybase PowerDesigner does not allow multiple definitions for the same business term even if they are in different categories. As a result, the tool would not allow me to create terms for “customer” in the Marketing and Finance categories even if they have different meanings. I found myself having to create workarounds like calling the second term “customer1.”
• Non-Sybase technical metadata – The Business Glossary does not let you work with technical metadata unless it has been modeled in Sybase. We had to establish workarounds like creating model stubs for a few tables in external applications and importing them into Sybase.
• Linkage to reference data – There really is no way to link a term to the associated reference data. For example, I would have liked to link a term called “gender” with the list of allowable values including “male,” “female” and “unknown.”
• Linkage to reports and applications – Other tools offer a desktop widget that links the business glossary to the report or application. For example, you can highlight a term in Cognos and then Shift+F5 to pull up the definition from the glossary. This is a great selling feature with business users.

Clearly, Microsoft Excel is the business glossary of choice for many enterprises. At the next level, a tool like the Business Glossary feature of Sybase PowerDesigner offers decent functionality to users who already have licenses. However, the tool is more targeted at data architects rather than business users. Finally, there are other tools like IBM InfoSphere Business Glossary and Collibra Data Governance Center that offer much more robust functionality for business users.

Information Asset Data Governance Industry Models^TM

Data Governance programs fail because they do not focus on business outcomes and take too long to deliver value. However, organizations can avoid these pitfalls by adopting a targeted approach to data governance.

The Information Asset Data Governance Industry Models^TM combine three approaches to data governance:

• People & Process – Leverage experience from hundreds of engagements across multiple industries as well as the learnings from Sunil Soares’ books on data governance
• Tools – Support Collibra Data Governance Center 4.0 and IBM InfoSphere Business Glossary 9.1
• Industry Orientation – Leverage pre-built templates for banking, insurance, healthcare, utilities, airlines, etc. to accelerate time-to-value

The Information Asset Data Governance Industry Models^TM include the following artifacts:

• Business communities corresponding to the membership of their data governance council
• Business definitions for critical business terms
• RACI matrix with custom roles
• Data Governance charter
• Sample data policies, data quality metrics, data rules
• Sample reference data sets

The following industries are covered:

• Banking
  https://www.youtube.com/watch?v=nRhYWO9Mg-I
  
• Insurance
  https://www.youtube.com/watch?v=EGwNXC1h_AY
  
• Healthcare
  https://www.youtube.com/watch?v=cRUgWSxrWYU
  
• Utilities
  https://www.youtube.com/watch?v=8giqC_pL1_A
• Airlines
  http://information-asset.com/index.php/airline-data-governance-a-business-driven-approach-using-collibra/

Information Asset, LLC
Harrington Park, NJ
www.information-asset.com

We are a boutique consulting and training firm focused on data governance and stewardship. Our competencies include data governance, data stewardship, metadata, business glossaries, data quality, master data management and reference data management.

We are looking for candidates for our 2013 Summer Intern program. Candidates will help build out our training and consulting methodology with a specific focus on verticals. We promise a tremendous summer experience for the ideal candidates.

The ideal candidates will possess the following qualifications:

• Candidates should have completed at least two years of an undergraduate program in computer science
• Candidate should possess excellent skills in Microsoft PowerPoint and Microsoft Excel
• Candidates should have a demonstrated ability to learn new software tools
• Candidates should ideally be located in the Eastern United States
• Prior experience as a research assistant is a plus

Please send all inquiries or a resume to Sunil Soares at sunilsoares@information-asset.com.

I’ve been doing some work with Collibra Data Governance Center and Semarchy Convergence for MDM. They are both great platforms. However, I got around to thinking that data governance for business terms and data governance for MDM appear to reside in two silos.

Many MDM implementations have very specific policies and rules that are rarely exposed to business users in an easily consumable manner. Here are some use cases where you could leverage a business glossary to support master data governance:

1. Agree on business terms relating to MDM
   The data governance team agrees on the definition of customer as “an individual or organization to whom we deliver goods or services for payment.” The definition for this business term may be populated in Collibra Data Governance Center. Collibra Data Governance Everywhere is a desktop widget that can point to the business glossary. A data steward can shift+F5 on the term “customer” in Semarchy and view the definition in Collibra.
2. Define data enrichment rules
   A data steward can define a data enrichment rule in plain English in Collibra Data Governance Center. This data enrichment rule might state that “the organization should leverage as an input the basic address information (address line, city, country and postal code) and output a fully geocoded address (street name, street number, longitude and latitude).” This data enrichment rule can then be implemented by an Enricher in Semarchy Convergence for MDM.
3. Create data validation rules
   A data steward can define a data validation rule in plain English in Collibra Data Governance Center. This data enrichment rule might state that “source address should contain at least one address line and either a postal code or a city.” This data validation rule can be implemented by a Validation in Semarchy Convergence for MDM.
4. Establish data rules to match records
   Once again, a data steward can define merge rules in plan English in Collibra Data Governance Center. A match rule might state that customer records will be matched if they belong to the same country, they have a strong similarity based on their name (greater than 65% using the Levenshtein distance algorithm) and they have a strong similarity on their address line and city (greater than 65% using the Levenshtein distance algorithm). This match rule can then be implemented by a Matcher in Semarchy Convergence for MDM.
5. Approve data rules to consolidate records
   Finally, a data steward can define consolidation rules in Collibra Data Governance Center. A consolidation rule might state that the surviving customer name across duplicate records should be the one with the most frequent occurrence. This consolidation rule can then be implemented by a Consolidator in Semarchy Convergence for MDM.
6. Adopt policies relating to hierarchies
   A risk data steward in a bank might create a policy in Collibra Data Governance Center that “customer hierarchies should be updated at the time of announcement of a merger versus the effective date of the merger.” The data steward can then manually update a customer hierarchy in Semarchy Convergence for MDM when one company announces its intent to acquire another.

There are several other examples of policies and rules that reflect the interplay between the business glossary and MDM. The crucial point is that policies, rules and terms provide a crucial bridge between the business glossary and the MDM hub.