Everything You Always Wanted to Know About Data Governance but Were Too Afraid to Ask

View all posts on Data Governance & Stewardship

About a month ago I said farewell to working as a government contractor and joined the DATUM team as a Proposal Coordinator. As I’ve been getting up to speed on our products and services, and all of the associated lingo funneling around inside the vortex of data governance, I find myself reminded of trying to sort through the boundless jargon of government titles and abbreviations that I thought I had left behind.

Before joining DATUM, I had never once heard the term “data governance” or “data stewardship” or “master data management.” Honestly, I had never even heard of “big data” (and how—if at all—does it compares to small data?)

And here we are, one month later, and to quote one of my esteemed colleagues, I’m already “drinking the DATUM Kool-Aid” and learning, as quickly as possible, to understand the vast new language of data governance (it reminds me of trying to learn Spanish during my freshman year of high school). Make no mistake: understanding data governance is akin to learning another language, and in order to better understand the roles and responsibilities associated with that language, it is important to first examine the key differences between data governance and data stewardship.

Data Governance vs Data Stewardship

The chief difference between governance and stewardship is that governance is a broad term defining the overall, big picture strategy of data management, whereas stewardship refers to the specific measures taken to reinforce that big picture strategy. If the two terms were nesting dolls, stewardship would be found nestled inside the shell of governance. Data stewards are often referred to as “keepers of the flame” in regards to data quality and governance. Some of the qualifications and characteristics of data stewards commonly include:

  • Understanding business and data management best practices, strategy, facilitation, and communication skills.
  • Defining business policies for creating, collecting, and storing data.
  • Documenting data sources and systems for recording data origins.
  • Adding and managing metadata.

Roles and Responsibilities of Data Governance
Versus Data Stewardship

Data Governance

Data Stewardship

Overall strategy and planning (governance is a process, not a project)

Execution of strategy and planning (operational best practices)

Enables/facilitates the creation of data standards, data quality scores, and metrics

Responsible for creating, storing, and collecting data

Defines goals and principles to guide a governance program

Responsible for documenting data sources and systems for recording data origins

Flexible enough to expand and contract based on specific project parameters (but rigid enough to maintain structure)

Ensure data quality, integrity, accessibility, and data security measures (solving data problems)

Governance is focused on people, policies, and processes used to manage data assets

Stewardship is tactical and specific—actions taken to remediate data issues

One important distinction of data stewards is that they do not assume ownership of the data nor do they have complete control over its use; rather their role is to ensure that best practice metrics are maintained consistently in collaboration with an organization’s data architects and administrators. Data stewards also strive to manage and bolster data quality within a specific domain he or she is responsible for overseeing. Stewards serve their respective organizations by providing a thorough, comprehensive approach to ensure data quality, integrity, accessibility, and data security measures.

Data governance helps enable the creation of data standards, data quality metrics and measures, and processes that solve data-related problems and address gaps in rules sets. Common steps in data governance include: defining goals and principles to guide the data governance process, establishing a communications plan, and creating a structure for different groups and advisory boards.

In a nutshell: governance is strategic, while stewardship is tactical.

While there is no textbook definition of data governance, the discipline itself can account for the storage, usage, and protection of an organization’s information, and can expand to specific areas of importance like data sharing, analytics, and security.

Gartner estimates that 90% of large global organizations will have a Chief Data Officer (CDO) by 2019. It is estimated that structured data is growing at a rate of 40% every year. Companies of all sizes—large and small—are in a constant struggle to manage the exponentially growing volume of data that they are generating. The bottom line: in the modern business landscape, effective data governance requires effective data stewardship.

Read our blog for more in-depth details on data governance. Contact us online or give us a call and discover how DATUM can help you with your data governance initiatives.

New Call-to-action