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Customer Experience and Design

Business Glossary – Sooner Rather than Later

If you are undertaking any significant data initiatives, such as MDM, Enterprise Data Warehousing, CRM, integration/migrations due to mergers or acquisitions, etc., where you have to work across business units and interface with numerous systems, one of the best investments you can make is to implement an Enterprise Business Glossary early on in your initiative.

An Enterprise Business Glossary is used to facilitate and store definitions and additional metadata about business terms, business data elements, KPI’s, and enterprise standard calculations (not every calculation will be a KPI, e.g., calculation for determining tax).

Why is an Enterprise Business Glossary so important? Data is meant to represent a real world business object and needs to be named and defined appropriately so it can be found, managed, analyzed, and reused. Semantic and naming confusion leads to dis-integration. Data entities in a Conceptual Data Model or a Semantic Model (e.g., using RDF/OWL) represent business objects such as Customer, Product, Vendor and so on. If you are trying to integrate data you have to understand what these terms mean – to the business units, source system, and the enterprise. Otherwise, there is a lot of flailing that will go on – data analysis, data modeling, and BI are all affected by lack of clarity in business terminology. Executive requests for analyses which seem straightforward (e.g., How many members do we have?) are hindered by the semantic confusion and variability found in our enterprises. Duplicate systems, data, and processes performing similar functionality require expensive resources.

Is the Enterprise Business Glossary the answer to all of our integration problems? Of course not, but if you don’t have infinite resources to throw at a problem, purchasing and implementing Business Glossary technology is a good way to be more agile and reduce costs. It is one of the least expensive and easiest enterprise data architecture components to implement and can have a very high ROI. It can facilitate many aspects of data governance and data stewardship, improve enterprise communication and collaboration between business and IT and between business units, lead to faster integration, provide for better knowledge transfer and retention (the definitions are stored in an enterprise repository rather than a spreadsheet floating around somewhere), and simplified workflow.

Poor metadata management is a leading cause of enterprise data failures – implementing an Enterprise Business Glossary should allow you to do some basic impact analysis as you can link glossary items to model objects, database tables, ETL processes, reports, cubes, and other implementation objects. This can enable your data stewards to measure where the data is used, where it comes from, and where it’s out of compliance.

I’m interested to hear your feedback or questions about Business Glossaries. For additional information about Business Glossaries, please download my whitepaper. You can reach me at, on Twitter at @pstiglich, or in the comments section below.

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