Why Bother with Data Governance?

September 17, 2020

Cognos Analytics (v11), Data Architecture, Microsoft Power BI, Predictive Analytics

Framework for Nimble Data Governance

In this on-demand webinar, we discuss the components of successful data governance. You’ll learn why governance efforts fall short and what foundational elements organizations often overlook or undervalue. You’ll come away understanding why good governance is so important to the success of BI in your organization.

Depending on whom you ask in the data world, the concept of governance may get called different things: an empty buzzword. A nasty four-letter word. A cornerstone element of a solid business intelligence implementation.

Love it or hate it, companies generally acknowledge the importance of having some degree of data governance. Despite its importance, many companies grapple with how to institute the “right” amount of governance for their organization.

Filtering the topic through the lens of his many years of experience with the Microsoft business intelligence stack, senior architect Shawn Alpay tackles these and other critical questions around instituting a manageable data governance program:

Why bother with data governance?

  • What are the warning signs that might suggest I need better data governance?
  • How do we implement data governance?
    • Data - seems obvious, but often taken too much for granted
      • Definitions, calculations, descriptions, tags, etc.
    • Process - far more important than the technology
      • Assess readiness, define principles, establish groups, etc.
    • People - so is this
      • Teams, roles, responsibilities, etc.
    • Platform - yes, of course the technology is important too
      • Architecture, development, security, documentation, etc.
      • Microsoft tools: Power BI, SQL Server, Azure, etc.
  • How can we implement data governance while staying nimble?

We know, governance has always seemed like a huge pain that takes too long. After all, you have projects to deliver. You'll learn the key components of good governance and how to make it (relatively) painless.


Shawn Alpay
Microsoft BI Senior Architect
Senturus, Inc.

Shawn is well-versed across the entire Microsoft BI stack and its wide range of offerings, having built ETL, data warehouse, reporting and analysis solutions from the ground up. In his various development and architecture roles, he often serves as the client’s project manager and business analyst, partnering directly with their team to gather requirements and deliver insight.




Love it or hate it, companies generally acknowledge the importance of having some degree of data governance to support their business analytics. Despite its importance, data governance is approached with a bit of complacency. Companies shy away from it because it’s labeled as too expensive to implement. Or too high of a hurdle to achieve. Or someone lived through a past attempt that went sideways, and it left a bad taste.

Whatever the reason, data governance gets the short end of the analytics stick. But the truth of the matter is that data governance is a cornerstone element of a solid business analytics implementation. In addition to mitigating compliance risks, good data governance supports decisions and internal processes, it also helps improve customer experience and create new products and business models.

It’s true that achieving good governance is not easy. It requires consideration, collaboration and commitment. It’s an intricate dance between people, process and technology. Even the best companies struggle to institute a viable governance program and are constantly fine tuning their efforts. But as the saying goes, nothing worth doing is easy.

In this webinar recording, we summarize the critical considerations around instituting a manageable data governance program.

What data governance does
  • Establishes one version of the truth
  • Increases trust across the organization
  • Establishes the business as data owners – not IT
  • Positions data issues as cross-functional
  • Treats data as an entity separate from its container(s)
  • Prioritizes measurements to define success/failure
  • Curtails security control issues (either too much access or not enough)
  • Reduces rework time and money (really!)
The components of data governance

Data governance requires thought leadership, it is a process, it is not a tool. There are four main components that all must be addressed to ensure success.

People. Data governance fails without personal ownership. It starts with an executive sponsorship team that endorses the mission statement, sets the culture and reviews decisions. A set of decision-making teams, with clear roles and responsibilities, must be determined at the onset.

Process. Process is far more important than the technology! Define the principles, determine a clear scope, create a roadmap with prioritized phases and schedule, and set clear roles and responsibilities.

Data. It seems obvious, but often the data is taken too much for granted. You cannot govern your data if you cannot define your data. After you determine which domains are to be governed, develop a data dictionary that details every datapoint.

Platform. The tasks must define the tools and technologies, not the other way around. All the other components listed above must be figured out first. This is the easy part if you are really committed to the people and process.

Nimble data governance

Data governance projects require iterations—they are never 100% done on the first pass. To be nimble, roll out the project in phases using an agile methodology.  We often find it useful to roll out Phase 1 and show off the data quality issues. To save time on the execution, invest the time upfront to define and document. 


According to advisory firm Gartner, enterprises are increasingly pushing for growth through digital transformation, which puts more pressure on increasingly antiquated existing technical frameworks. Gartner believes that “through 2022, only 20% of organizations investing in information governance will succeed in scaling governance for digital business.”

Data governance takes hard work to achieve, but it is well worth the investment. So, if you are going to do it, do it right. No consultant can do it all for you—pulling together the key governance components of people and process is a bit of a “family affair” and no one knows your organization like you do. But knowledgeable consultants can serve as arbiters, help facilitate communications between stakeholders, help set up a solid framework and get you started on the right path in this most worthwhile journey.