Business Glossaries and Metadata: The “Value” of our Data Consumers

15-SEPCOL04FRYMAN-edTraditionally, many Data Governance organizational activities and processes have been focused on the infrastructure efforts to create, maintain, and improve our critical data to the greatest extent possible. These “infrastructure” activities often start with creating an organization to manage and improve data, build business terms and create metadata about those terms, building out a data dictionary, identifying the data supply chain and authoritative sources, improving data quality, managing data issues, and so on. After all, this has been the goal of the data management industry for many decades; just read the DAMA DMBoK. We all agreed that it was important to complete these infrastructure activities as our Data Consumers were crying about the poor state of our data.

The efforts of Data Content Owners, Data Custodians, and Data Stewards are critical to achieve the most accurate, complete, and timely data possible. There is no question that all those efforts are essential. Yet, let’s ask why we invest all of that time, money, and technology? The answers can likely be summarized as we invest all that effort to have the best data available for all the business, compliance, and analytical usages needed by our Data Consumers.  Yet, those traditional data governance approaches have ignored the importance of the Data Consumer. Often the Data Consumers have not even been listed in the organizational picture. That is a “build it and they will come” approach that we know often results in failure.

Most industry experts will say “data is the new currency, and its value is in its usage.” The more we can use our data for diverse processes and analytics, the greater the potential for achieving substantial economic benefits from that data. No question here again. Yet, some data governance teams do not recognize that Data Consumers have significant accountability and responsibility to help achieve the most accurate, complete, and timely data possible. This is a mistake. Let me explain why.

First, what are some of the general requirements of Data Consumers and how can data governance support those?

Generally, Data Consumers should be asking questions such as the following:

  • What data is available for me to conduct my business processes?
  • How has this data been defined; is it defined like I think it is?
  • What is the quality of the data; does it meet expectations for my processes, and can I trust it?
  • Where did it come from? Is this a source I can depend upon?
  • How timely is the data in this source?
  • What controls have been applied to this data, and does it meet our industry expectations for controls compliance?
  • How do I get access to this data?
  • What are the usage constraints (security, privacy)?
  • Who else uses this data, and for what purposes?
  • What is the update or refresh frequency for this data?
  • Who do I talk to for further understanding?

All great questions, right? The need to achieve answers to these questions drive the reasons why we invest in data governance resources, processes, infrastructure, and solutions. To answer these questions, we may need to establish all of the following:

  • Data Governance organization of Data Content Owners, Data Custodians, and Data Stewards (who to talk to)
  • Business Glossary for Critical Data (definition, understanding, business rules)
  • Catalog of all assets and relationships for the Critical Data Terms (where does it come from, when, timeliness, controls)
  • Data Catalog for Critical Data (what data is available, from where, how to access)
  • Data Sharing Agreements (specific usage constraints and sources for data)
  • Data Quality Metrics (what is the quality for accuracy, completeness, integrity, etc.)
  • Reference Data Management for Critical Data (what are the values and what do they mean)

We must recognize that Data Consumers are not just casual users of our data. As I said, the value is in the data usage. Thus, Data Consumers should be recognized in the Data Governance organization for the responsibilities and accountability they have. To make a point, I’ll borrow the term “it takes a village” to achieve governance of our data. Data Consumers are members of our data village.

Data Consumers should be recognized for formal accountability and responsibilities, including:

  • Participate in the definition of business terms and definitions to ensure usability within their business processes. They are responsible to participate in this activity.
  • Participate in the identification of business rules, data quality rules, and data quality thresholds. They are responsible to participate in these activities.
  • The definition of data quality “fit for purpose” is a combined responsibility of all Data Consumers to ensure appropriate data content and values for their specific business processes. These are requirements that must be met by the Data Owners and Custodians whom are accountable for collecting the requirements and then achieving the results.
  • Participate in the definition of Data Sharing Agreements so Consumers understand the authoritative source of data and the data constraints, such as security and privacy, for its usage.
  • Data Consumers are accountable for the proper usage of data as defined in the Data Sharing Agreement. Compliance to data governance policies and Sharing Agreements should be measured by the data governance team.
  • Participate in the resolution of data issues as requested by the Data Owners.
  • Identify data issues and bring to the attention of the Data Owner as soon as they are recognized by the Data Consumer.
  • Consume data only from authoritative sources identified by the Data Owners or Data Governance team. Identify data needs that are not supported by authoritative sources.
  • Identification of data control requirements that should be implemented by the Data Owners to ensure quality and integrity in the data supply chain based upon the compliance requirements of the Consumers’ business processes.

All Data Citizens (of our data village) are Data Consumers at some point in time. We all need to believe we are in the village together and all of our actions contribute to the improvements in the value of our data. The Data Consumers that conduct reporting and analytics are critical contributors to bridge the gaps between operations and analytical usage of our data. It is those Data Consumers that have the greatest data usage requirements and need to define the quality “fit for purpose.”

The Data Consumer role–and all individuals in the role—should be formally recognized, as they have responsibilities and accountability in the governance of our data as noted above. It is important to recognize the Data Consumer’s contributions in our governance processes. As we begin to think about Data Governance 2.0 methods and approaches, I believe we will recognize the significant role our Data Consumers provide. We will establish the expectation that the Data Consumers must be a part of the solution to achieve great data governance and improve the value and benefits we receive from our data. Please give your Consumers a seat at the table. It is OK—stay calm, and allow your data governance to prosper.

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Lowell Fryman, CBIP-CDMP

Lowell Fryman, CBIP-CDMP

Lowell is responsible for directing thought leadership and advisory services in the Customer Success practice of Collibra. He has been a practitioner in the data management industry for three decades and is recognized as a leader in data governance, analytics and data quality having hands-on experience with implementations across most industries. Lowell is a co-author of the book “Business Metadata; Capturing Enterprise Knowledge”. Lowell is a past adjunct professor at Daniels College of Business, Denver University, a past President and current VP of Education for DAMA-I Rocky Mountain Chapter (RMC), a DAMA-I Charter member and member of the Data Governance Professionals Organization. He is also an author and reviewer on the DAMA-I Data Management Book of Knowledge (DMBOK). He focuses on practical data governance practices and has trained thousands of professionals in data governance, data warehousing, data management and data quality techniques. You can read his Data Governance Blogs at,

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