Data Governance Content Creation Methods

Data Governance Content Creation Methods

StockSnap_IGOG2UDSZP_ContentCreationMethods_Typing_BPThere are many methods to create data governance content at an organization. Some methods are easier than others. Some methods require a great deal of human touch whiles others do not. Some methods require a knowledgeable person to handle the request for content. And usually, one piece of content created will lead to other pieces of content to be created. A successful organization will probably use all the different content creation methods. The content can be data deliverables such as definitions, data system inventory entries, data quality rules, report specifications, and reference data. In this blog post we will discuss the various methods of creation (automated, imported, curated, and emergent).

Here are the four data governance content creation methods (automated, imported, curated, and emergent) in more detail:

  • Automated discovery and synchronization method – Examples involve having a solution like the Data Cookbook that can automatically, without human involvement, pull in data model changes from data systems, notify if reference data values change, and having data quality rules that will notify if there is an issue. We do recommend doing this method first, if possible, because there is no reason to wait as it does not require human effort to do it on a regular basis. Sometimes there is a bit of politics of getting access and connectivity. Usually involved in this method for initial setup are IT staff members and a data steward assigned to the area involved. Sometimes these automated items will create requests that need to be curated.
  • Bulk imports method - You have an existing business glossary in a spreadsheet. Or you have data standards documentation from some regulatory or consortium organization. These are items you can easily import into your data governance knowledgebase. An import gives your content creation a quick start and does not require human curation. Another bulk import might be just importing information about your reports, just the existence of your reports, which is useful for an inventory standpoint. But often it is lacking the contextual information about the purpose and the value and the definitional information around these reports. And the way that this thing calculates that, is that right, versus this other way that this other report that calculates the same thing differently. Or here are two reports that have two labels that say that they are the same thing, but they do not appear to be the same thing. But are they? Sometimes these imports will create requests that need to be curated. Usually involved in using this method for the initial import are IT staff members and a data steward assigned to the area involved.
  • Curated or requested method – There needs to be a process where individuals can request such things as new reports, new glossary definitions, new data quality rules, changes to reference data, updating specifications on an existing integration, and  reporting a data quality issue. A request should be routed to the appropriate data steward who will handle the request. Usually, these requests lead to content creation and this content is put into a data governance knowledge base. This creation takes effort and needs knowledgeable individuals. For example, you are documenting a report, and on it is employee status, you need to curate and create the glossary definition for employee status. And this definition will be used in the future by others. Or you get a request for access to a data system, and you realize that there is no entry in the inventory for this data system. You create the inventory entry so that future requestors know how to get access. Data governance content creation involves organizing and managing the content so that it can be used again in the future by having it easily found in a data governance knowledgebase by data consumers. Usually involved in this method are the requester and the data steward handling the request.  Additional information regarding data request process can be found here.
  • Emergent content method – One thing leads to another. Often a data steward will realize while working on one content piece that other content is necessary or that certain content needs to be improved. This emergent content comes from working on a requested, curated, item. For example, when defining one glossary definition for a report, you need to define five others, because to understand what your current employee status is, you need to define what general employee statuses are.  Emergent content is part of a customer service approach to creating data governance content. You want constant improvement of your data governance knowledgebase and this emergent content fills in the missing pieces.  Usually involved in this method is the data steward who is assigned the request.

These are the methods that are used to create data governance and data intelligence-related content. Look for bottlenecks in your content creation methods. Maybe it is that there is no data steward assigned in that functional area. Maybe it is a difficult request process (no easy point of engagement) for data consumers. Maybe you have difficulty with definition collisions. Maybe folks are not educated on the points of engagement. Maybe you are trying to use committees to create content. We feel that data governance content is only valuable if it is used and the only way to make sure that it is used is if it was requested. The only situation where this might not be the case is if the content is necessary to satisfy an auditor, so they go away. Then fine, just create that content and do not care if anyone uses it or not.

Hope that this blog post gave you some ideas in your data governance content creation methods. If you would like additional resources (blog posts, recorded webinars, or videos) on data intelligence or data governance then click here.

IData has a solution, the Data Cookbook, that can aid the employees and the organization in its data governance, data intelligence, data stewardship and data quality initiatives. IData also has experts that can assist with data governance, reporting, integration and other technology services on an as needed basis. Feel free to contact us and let us know how we can assist.

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Jim Walery
About the Author

Jim Walery is a marketing professional who has been providing marketing services to technology companies for over 20 years and specifically those in higher education since 2010. Jim assists in getting the word out about the community via a variety of channels. Jim is knowledgeable in social media, blogging, collateral creation and website content. He is Inbound Marketing certified by HubSpot. Jim holds a B.A. from University of California, Irvine and a M.A. from Webster University. Jim can be reached at jwalery[at]

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