Data Governance centrally defines common data management principles for organisations. In this article, Advian's Lead Data Analyst Eeva Randén explains what data governance is in practice and how you should utilise it in your daily work.
Data Governance – What it is and what it isn't
"Tame your data! Harness the power of data!" says every other IT firms' slogan. As if data were a force of nature or a wild animal racing through the woods, whose properties humans can hardly influence, but with persistent work and proper tools, can barely make some use of it.
In our imagination, data seems almost random, perhaps the result of some mystical events, and therefore we do not feel that we have a real influence on, for example, its quality or meaning.
/ We like to call ourselves data driven
As we all know, data is at the heart of business, and we like to call ourselves data driven. In practice, the job descriptions of data experts are largely defined by the characteristics of data. However, not always in the desired way. Days go by while correcting errors, hunting for incomplete or varying descriptions, and investigating due to unclear responsibilities. Indeed, the everyday work in the organisation is strongly driven by data.
Good servant, but a bad master – enabling data management with data governance
At its core, data governance means defining common data management principles for an organisation. In practice, these are different standards, processes, and descriptions of roles and responsibilities.
Sounds boring? At first, yes, I think so too.
Fortunately, I don't think that description really captures the essence of data governance. People is what's at the core of data governance, and somewhat exaggeratedly, giving control back to them. By this, I mean concrete actions and deeds that make the properties of data visible and manageable throughout the entire data lifecycle. Employees no longer bend over backwards for data that's out of control, but do exactly what is needed to make data known and managed.
What are we really aiming for when we define roles, responsibilities, common principles, and standards? We want to offer guidance to those in charge of data, so that they are able to control and manage it.
Instead of just saying, "You are now responsible for the quality of data in this system - good luck!", we give the data owner a concrete list of actions that make the data:
- High quality
- Valuable to business
Regain the power
As said, data governance is not a standardisation process of framework principles, but the returning of power to the people. We give the employees responsible for data the tools and opportunity to influence data and its properties. This is done through centralised data governance so that we can trust that all other data owners and those responsible for data quality are doing the same things in the same way for their own data across the organisation.
/ Data can be a good servant but a poor master for an organization
When we work systematically, we create data that doesn't require us to tame or harness it. Data is no longer the result of mystical forces that leaves us humans trying to make sense of it, and race against accumulating errors and unclear data streams.
When we own and lead our data, we understand both its content and its properties, and we can confidently utilise it. Effective data management is a prerequisite for data-driven decision making. Data can be a good servant but a poor master for an organization.
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