Data Governance: Benefits and Best Practices
What can data governance do for your enterprise, and how can you improve your data governance program? Semarchy’s Michael Hiskey offers some perspective.
In an age when regulations such as the GDPR impose ever-greater penalties, data governance‘s importance has never been higher. What benefits can you expect, and how do you get started?
For answers, we spoke to Michael Hiskey, head of strategy at Semarchy, which bills itself as “The intelligent data hub company.” Hiskey thinks of his role as “chief product evangelist” and “storyteller of client success.” Among the topics we discussed — best practices for data governance.
Upside: From your perspective, what are the three key benefits of a data governance program?
Michael Hiskey: I’d put accessibility at the top of my list. In order to govern data, it needs to be brought into one place (either persisted in one place or virtually connected there). Bringing data from silos into a governed environment, which is part of master data management, makes it possible for it to be accessed easily by staff who can ascertain value from it.
Second, I would say security. Once you have data all in one place, it becomes a pressing concern to control who has access to it. Governing data makes it more secure and adds auditability.
Uniformity is the last key benefit. Data quality and enrichment should go hand-in-hand with governance, as does the normalization of reference data. Having uniform options in drop-downs, for example, makes analyzing, reporting, and decision making easier.
That’s part of the uniformity I mentioned. Duplicates, errors, and bad data are surfaced as part of the governance process. The addition of data lineage (where did this bad data come from?) and auditability (who made changes to this data/field and when, under what authority?) improve the quality and utility of the data in question.
In short, business value. Data project holders want governance programs but often lack the ability to state in simple terms what value they will drive for the business. One of the hindering points is that effective governance can’t be obtained without also tackling MDM, data quality and enrichment, and workflows. This is closely related to data catalog, metadata management, and business glossary efforts — which also fall short.
Cobbling together many point solutions is rarely effective, and the project implementation timelines often delay ROI beyond the reasonable expectations of the business.
