I was asked the other day: what is the difference between data governance and data management. And why does it matter? To be honest, what truly matters for an organization is not the definition of terms but rather how efficiently and effectively the organization uses data for decision making. Whether an organization correctly defines data governance or data management matters only if doing so helps the organization maximize its use of one of its most important assets: its data.
However, I do think there is value in defining and contrasting the two terms for one reason. Not understanding the differences between the two and incorrectly setting up programs to govern and manage your organization’s data can lead to improper and ineffective implementations of your data governance and/or management programs.
Many people – even experts – do not correctly define data governance. Merriam-Webster defines governance as: The act or process(es) of overseeing the control and direction of something. Simply put – governance is a system relating to how decisions are made. Data governance is then the system put in place to make decisions controlling data.
Data Management, on the other hand, is the practice of collecting, organization, protecting and storing an organization’s data.
So, within a data governance program, you would make decisions about how data is managed. And, in the data management program, you would implement those decisions.
Yet, if you look at this article from dataversity:
https://www.dataversity.net/data-governance-vs-data-management/ Or this posting: https://www.to-increase.com/master-data-management/blog/data-management-versus-data-governance
You would think that Data Governance is a subset of data management. These articles claim that the control of data is just one aspect of an overall data management program.
Why is this view incorrect?
Look at the following two diagrams:
Both diagrams show Data Management as the Center of the data universe. And they show data governance as only one component of data management. This view, I would argue, is an IT-focused view. This view puts Data Governance on the same level as data quality, security, master-data and integration. However, a good data governance program makes decisions about to what levels data should be cleaned within your environment. Data Governance makes the decisions about who should have access to which pieces of information. A data management effort, then, would implement those decisions.
By making Data Governance a single component of Data Management we make the entire picture / architecture an IT focused initiative. And while the management of data maybe should be a technical endeavor, the decision-making process dictating what happens with an organization’s data should NOT be solely an IT activity. What would your company say if IT wanted to make decisions on how money was managed? There would be a revolt. IT certainly should be involved in providing the tools, software, security to the effort of managing money. But the decision-making process of managing money should be controlled by and involve others in the company. In the same way, the decision-making process for managing data – another company asset – should also be controlled by / involve others in the organization outside of IT. IT will provide the tools, software, security etc. towards facilitating the implementation of the decisions made by a data governance program.
Info-Tech’s diagram below, I believe, comes closer to a positive framework that has better potential to be successfully implemented.
This framework shows Data Governance as the center piece for data enablement. Which is the proper way to think about creating an entire effort around the controlling, managing and utilizing the data within your organization.
At Pandata Group, we think about the relationship of data governance to data management as what is pictured below:
Data Governance determines how decisions are made about each of the pillars within a data management program. And an organization’s data governance program should involve people in key roles (i.e. Owners, Stewards, etc) from all aspects of the business: Finance, Operations, Sales, Marketing, HR, etc.
In our next blog post, we will discuss how to start implementing a data governance program to build your organization's analytical capabilities.
By: Jason Fishbain | Data Governance Practice Lead
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