Getting Started with Information Governance: The Glossary Approach

Shared definitions of key terms help align business and IT and make analysis more meaningful and trusted

Program Director, Analytics Platform Marketing, IBM

The road to excellent information governance is typically a long one, with many twists and turns along the way. There are business objectives to formalize, strategies to create, organizational issues to address, and implementation plans to create. But the length of the road ahead should not be a deterrent to getting started. Benefits can be derived even in the early phases.

The potential starting points are numerous, but this column will focus on one: creating a business-critical glossary of terms. At the recent Information On Demand 2012 conference, I spoke with several customers who had chosen this starting point, and then I reviewed the progress of two organizations in detail during the technical sessions.

Business glossary: A key to confidence in your data

In an age when business success often depends on the analysis of trusted data, the organizations at the conference were pressed to understand the real meanings of their key data elements. With data spread across an increasing number of sources, they wanted to accelerate the understanding of data and its lineage—increasing trust and tapping into the value of their critical data assets. They found that establishing a common business language in the form of a business glossary could align business and IT goals and create a shared sense of ownership of business metrics.

Why start an information governance process by creating a glossary? One reason cited by those who have done it is that it’s a manageable undertaking. It requires collaboration with multiple parts of the organization, but it doesn’t require organizational upheaval or enormous financial investment.

Another reason for choosing this path is the opportunity for near-term benefits. Even if the organization never reaches its ultimate governance goal, a glossary shared across the company can make many projects easier while making reports and analysis more meaningful and valuable to the business.

A third reason is that other companies are already doing it and deriving benefits. If they are your competitors, they may be jumping ahead of your organization in leveraging their own critical data. If not, you have an opportunity to gain an edge without taking a big risk by taking advantage of best practices from other organizations.

Implementation patterns

I found similarities in the implementation patterns of the two focus organizations—one in the insurance sector and the other in telecommunications.

The insurance company planned its course within the context of the Data Governance Council Maturity Model and created its business glossary to support an electronic data warehouse (EDW) implementation. Its process included the creation of the glossary, the rollout to users across the entire enterprise to support enterprise-wide reporting, and the creation of hundreds of business lineage mappings.

After creating its broad framework and organization focused on the management of enterprise data assets, the telecommunications company kicked off its implementation by defining business metadata first, and then technical metadata. It standardized definitions, created a central repository, and exposed data lineage to business users.

From this tiny sample, the following general pattern emerged:

  • Creation of an organization to guide the governance process
  • An implementation focused on shared definitions of key terms across business and IT, exposure of data lineage, and engagement of business as well as technical users
  • Movement to subsequent phases of information governance such as data quality, reference data management, master data management (MDM), data lifecycle management, and security
  • Ongoing engagement of the leadership group through planning, guidance, and evaluation of the process


With this approach to data governance, you’ll need to get started by considering a rich glossary tool such as IBM® InfoSphere® Business Information Exchange.

IBM InfoSphere Business Information Exchange is designed to support governance initiatives by helping you understand your information and align business and IT goals using a common business language. It not only accelerates the creation of a business glossary but also outlines the lineage of fields from applications, reports, or data warehouses back to source systems. It supports governance policies and rules—so you determine how information should be structured, stored, transformed, and moved, and then define measurable criteria for assessing compliance with business objectives.

Other components of the InfoSphere portfolio can help simplify subsequent phases of an information governance initiative at the appropriate times, with tools designed to support data quality, MDM, data lifecycle management, and data privacy and security.

Which approach is right for you?

Is a pattern that starts with metadata and the creation of a business glossary the right one for your organization to follow as you create your own data governance pathway? It is certainly one approach worth considering. In future columns, we’ll look at other approaches to getting started with data governance. I welcome your input on what has or has not worked well in your own organization. Let me know in the comments.

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