Data Governance vs. Data Architecture

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Data Governance vs. Data Architecture

“While Data Architecture focuses on technology and infrastructure design, Data Governance encompasses the people, the process, the workflow, as well as the architecture needed to support governance. So, even though Data Architecture is critical to Data Governance, it’s a small piece of a wider whole,” said Donna Burbank, Managing Director at Global Data Strategy. She likened the difference between Data Governance vs. Data Architecture to the elephant in the old story about perspective:

“Five old men are looking at the elephant. One sees the tail and he thinks the elephant looks like a rope. One sees the trunk and he says it looks like a snake, and one sees the foot and he says it looks like the trunk of a tree, and they are all right.”

Each person sees the whole elephant from their own unique, but limited position. “I think with Data Governance, that’s often where there is confusion for a lot of technical people,” she said. Some IT staff see Data Architecture as the same as Data Governance, but it’s much broader than that. Once you include the organization, process, people, and culture you’re far more likely to succeed.

 “Data Governance is the overarching framework of which Data Architecture plays a part. I see Data Governance as being broader, in that it encompasses the organization, the people, and the process, and – very much so – creating a data-driven culture,” she said.

Figure 1: Data Architecture is Part of a Wider Data Governance Framework (Credit: Global Data Strategy)

The concepts are interrelated, so processes that may appear to be wholly related to Data Architecture can play a key part in Data Governance. Data entry, for example: “It’s governance if you are typing in customer data upfront, and you are typing it wrong, [because] that’s going to impact things downstream.” A lookup table created out of a governance process can support referential integrity by making it easier to enter customer data correctly, she said. “So, it’s that back and forth between architecture, and people, and process.”

Data Architecture and Data Governance “give each other teeth,” she said. “Data Governance can set the rules around Data Architecture and often, IT embraces that because they love to have someone they can escalate these issues to.”

Technology provides teeth through the structure or boundaries inherent in the technology.

“You could have a very good rule on the business side saying ‘these are the valid values’ for a certain field, but unless your Data Architecture supports that, it’s just a rule and people can break rules. So, architecture and governance not only support each other, but also help each other be more effective.”

Growing Interest in Old-School Concepts

Burbank sees interest in AI and predictive analytics driving a resurgence of interest in foundational concepts like Data Governance and Data Architecture: “You can’t do all these new hot things unless you have good data. It isn’t old versus new, or old school versus new school; it’s that you need these foundations.”

To those who have been in the industry a long time, it may seem like old stuff, she said:

“Some of the companies that have invested in architecture and governance already are able to implement some of these newer technologies more easily because they have that good data foundation. Those that don’t often have to catch up.”

Data Governance vs. Data Architecture: Which Comes First?

There are differing theories about where to start, but Burbank recommends starting with an in-depth Maturity Assessment based on a framework that shows how vision and strategy relate to tools and technology. She suggests initially working through each box in the framework. “These are all very simple questions, but just two questions in each box can speak volumes,” she said.

  • Why are you doing this and who cares?
  • What problems does it solve?
  • Who are going to be your key stakeholders?
  • Who’s going to be your executive champion?
  • What’s your ROI?
  • What governance organizations already exist and who is involved?
  • How do you measure what data is good or bad?
  • How do you track results?
  • Do people have a positive perception of Data Governance?
  • Do they see it as a burden?

“Simple questions like those at the top of that pyramid – those are what’s most important to ask because they drive everything else.” The tools and technology section can almost be a checklist, she said. Ask questions such as, ‘What data do you have and where is it stored?’ and ‘Is there a data model?’

“You don’t have to start with a huge assessment. A couple of questions in each one of those boxes is a great way to start, and people can probably do much of that themselves,” she said. Burbank’s clients get a far more extensive set of questions, with detailed steps. “For organizations and people, do you have a steering committee?  Does that steering committee have actionable results? It’s not just ‘yes’ or ‘no’: There’s a lot of detail.”

The granular nature of the assessment not only shows where the gaps are, but helps uncover reasons for those gaps. “A lot of people have a steering committee but nothing gets done, so how is that steering committee set up? How is Data Stewardship set up?” Both areas need to be equally strong, she said. “If there is a gap in any one of them, it could be that you have all the tools and the technology, and all the processes, but the culture isn’t there.” The end result for her clients is a color-coded Maturity Assessment, with areas of strength in green and areas for improvement in red.

Encourage a Strong Data Culture with a Quick Win

People can often see Data Governance as a burden but it doesn’t have to be, she said.

“How do you get people excited about it? Well, actually, it happens all the time. Start with a quick win, [and you can] actually have people asking, ‘Can I be a part of Data Governance?’”

Burbank suggests picking something small “that can show benefit to a lot of people.” A retailer, for example, could define their customer lifecycle and document process and data flows to track the customer when they first look at the product, when they buy it, when they renew it, and when they tell their friends on social media.

“If we just got the email address right across all these silos, and it was consistent, we could track our customer from when they first gave us their email address, to when they sign up for the loyalty program. If we all communicated, think about how [much] better this would be. And then if I could get purchase information from another team, the value of transcending those silos becomes clear.”

It’s the “what’s in it for me?” question and it’s about making it not overwhelming, because no one wants to have this massive project that’s going to take a lot of time driven by somebody else, but if you can find that thing that everybody needs. “There’s the quick win,” she said. “And then people definitely want more.”

Data Governance vs. Data Architecture: What’s More Important?

Burbank shared a story of two clients who landed on opposite sides of the Maturity Assessment.

“One group had their business goals and objectives tied into some regulations and into their marketing campaigns. They had multiple groups supporting it. It was marketing, it was engineering, and it was legal – they had several groups wanting Data Governance. They had their goals defined but everything else was a bit weak. They hadn’t yet started their committee, and they didn’t have any tools in place.”

Their goals were good, she said, but on their assessment, they had only one green section and everything else was red. “They were so despondent, and I said, ‘No, this is the best place to be because you have the right goals.’” The other company’s assessment showed mostly green for technology, architecture, etc but they hadn’t committed to a common goal and buy-in across the groups.

“They had every tool you could imagine and they had everything in place. Pick a tool – they had six of them – and they had multiple competing technologies, but they didn’t have that common buy-in in the culture and that was their red. Fast forward a year – the folks that had the right drivers and the right people in place were much further ahead because they had won the hearts and minds.”

Look at it holistically, she said. “It’s that part of the elephant – some people might think they have Data Governance, but they haven’t really thought about the culture around it, so they’re not done yet.” The best place to start, she said, is with getting people aligned. “When people have the right goal, you can do anything, right?”

Photo Credit: spainter_vfx/

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