This is the fifth in a series of six posts on metadata collaboration from David Loshin. Read the previous post and the next post in the series.
In my previous post, we discussed the need to review business glossary terms and data elements and their corresponding definitions to determine where there is sufficient similarity among metadata concepts to harmonize their definitions or if their definitions are distinct to take the steps to ensure their differentiation. However, from a practical perspective, the mechanical processes of metadata harvesting, assessment, collation, review, and harmonization are only relevant when business users are paying attention to the outcomes.
The conundrum is that the criticality of an accurate and synchronized metadata repository is only apparent when there is a business need for business term reconciliation to address perceived inconsistencies, such as when two different reports show completely different numbers of current customers. The absence of any inconsistencies hides the criticality, which suggests that the need for accurate metadata is constant, but its apparent relevance is somewhat fleeting. The task for the information practitioner is to build awareness among the business data consumers to highlight the real motivations behind effective metadata management: continuously satisfying the needs of the business data consumers without forcing them to become experts in data management techniques.
Engaging the business users begins with education in demonstrating that business metadata is the lingua franca for enterprise communication. Reports, presentations, spreadsheets, and documents are rife with business terms that are ripe for misinterpretation. Customer, product, part, site, vendor, and employee – these are all examples of business terms used almost universally yet are seldom if ever clearly defined. It would be surprising to review even a small handful of corporate reports without finding discrepancies in the presumed semantics of commonly-used business terms; pointing these out to key business data consumers is a good first step in building awareness about semantic inconsistency and the need for metadata management and harmonization.
Reach out to the business users and engage them on their own terms:
- Select a sample of enterprise information products: reports, presentations, or documents;
- Scan through the artifacts and select the most frequently used business terms;
- If possible, provide the most reasonable definitions of these business terms as they are used within the context of each artifact; and
- Present the variant or discrepant definitions to the owners of those information products.
The last step is the most important:
- Ask the data users about the business impacts of the indeterminate semantics.
Ideally, the business users will immediately provide feedback about potential issues, or they will be intrigued and will investigate the possible impacts on their own. Either way, highlighting the risk of business impact is a good first step in involving business users in establishing processes for research the candidate terms and concepts for a business term glossary. The next step is to foster a cultural shift in establishing collaboration among the business users and information professionals to synchronize critical business terms, their definitions, and their uses across the application landscape.
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About the author:
David Loshin, president of Knowledge Integrity, Inc. (www.knowledge-integrity.com), is a recognized thought leader and expert consultant in the areas of analytics, big data, data governance, data quality, master data management, and business intelligence. Along with consulting on numerous data management projects over the past 15 years, David is also a prolific author regarding business intelligence best practices, with numerous books and papers on data management, including the second edition of “Business Intelligence – The Savvy Manager’s Guide”.
David Loshin, president of Knowledge Integrity, Inc. (www.knowledge-integrity.com), is a recognized thought leader and expert consultant in the areas of analytics, big data, data governance, data quality, master data management, and business intelligence. Along with consulting on numerous data management projects over the past 15 years, David is also a prolific author regarding business intelligence best practices, with numerous books and papers on data management, including the second edition of “Business Intelligence – The Savvy Manager’s Guide”.