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There are two big problems with data governance today: The first is data; the second is governance. No, I’m not trying to be cheeky. Data is a problem, because every day it grows further removed from the comfortable confines of relational database rows and columns. There’s simply too much highly varied data plowing through the enterprise at an ever-increasing velocity.

Data governance efforts may strive to tame these growing sets of data, but too often governance policies and procedures fail. It can be comforting for a CIO to tell her CEO that she has a data governance team in place to bring security and process to a company’s data, but her company is still very likely among the 90% that told Gartner their data governance projects had failed.

Yet all is not lost. In fact, today’s trends in data governance suggest enterprises are learning from past failures and are starting to implement data governance that is less focused on tools and more focused on people-oriented processes. Such processes will increasingly span the entire organization rather than sitting within an isolated team. But this isn’t all that’s happening in the formerly staid world of data governance.

Data governance today

Data governance dictates how an organization manages its data throughout the data’s lifecycle, from acquisition to disposal, as well as the different modes of usage in between. Though data governance involves tooling, it’s much more than that: It also involves the processes people must follow to ensure the security, availability and integrity of data.

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Traditionally, data governance was a highly centralized function that was more focused on controlling data than enabling innovation. This has changed and, in some organizations, it has changed dramatically.

Due to “varying levels of uncertainty in today’s world,” argued Saul Judah, VP analyst at Gartner, data governance needs to embrace “speed and agility,” which has rendered “traditional approaches to data governance … obsolete.”

As such, modern data governance tends to be driven by principles that link data to a business case so the governance model can flexibly respond according to business needs. Importantly, modern data governance never forgets the people involved, helping them to protect and prepare data for enterprise use.

Top trends in data governance

It’s not just about risk

Data governance has traditionally taken a top-down approach, identifying potential risks and attempting to shutter access to data. This was intended to ensure compliance with rising regulatory demands.

Today’s data, however, gains value through its use in machine learning algorithms and other revenue-generating activities, making old-school data governance obsolete. In fact, according to a 2022 Zaloni survey of data governance professionals, the two primary reasons for increased investment in data governance are data quality (74%) and analytics/BI (57%).

As Forrester has highlighted, leading data governance tool providers have “added collaboration features to get data governance closer to where the tribal knowledge and expertise lives.”

To make data more broadly accessible, data governance tools are increasingly incorporating policy and stewardship management capabilities, thus simplifying access for a wider variety of user roles. Additionally, data governance tools often have AI/ML and associated capabilities built in from the start.

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The goal is to democratize access to accurate, consistent data across the enterprise to aid in business decisions. It’s no longer a matter of de-risking data. Indeed, one of the big, underlying trends here is increased data literacy efforts across organizations. While there are still steering committees and stewards to shepherd data, the objective is to get data safely into as many hands as possible.

From regulatory compliance to data quality

Data quality efforts show up as another big trend in the data governance world. While it’s absolutely the case that much of the recent interest in data governance was sparked by proliferating regulations, many organizations are looking at their more holistic data strategy to keep up with regulatory compliance. During this shift, it’s become even more critical for enterprises to achieve improved data quality. In fact, as Zaloni’s survey revealed, it’s the primary factor motivating enterprises to get serious about data governance.

However, as Gartner has outlined, improving data quality is more a matter of process than tooling. These processes include defining “good enough” standards for data quality and making it a recurring agenda item when the data governance board meets. Such processes help to ensure that employees can trust the data they’re using to fuel an array of operational use cases, but especially AI/ML With AI and ML technologies growing their enterprise prominence and use cases, data consistency, integrity and overall quality continue to increase in business value.

The cloud changes everything

Underlying many of these changes is the reality of modern cloud computing. Though the cloud still represents a relatively small percentage of overall IT spending, it consumes a significant share of net new IT spend. Directionally, it’s where the greatest share of IT spending is heading.

Data governance shows up in the cloud in two ways. First, more data governance tools now run in the cloud. Second, more of the data that requires governance strategies is coming from cloud-based applications.

As IDC has predicted, by the end of 2022 over 90% of enterprises worldwide will rely on a mix of on-premises/dedicated private clouds, several public clouds and legacy platforms to meet their infrastructure needs.

This is good and bad. It’s good because it suggests enterprises are taking data governance across hybrid architectures seriously. But it’s bad in that, as revealed in Zaloni survey data, few enterprises feel they have the “skills needed to manage new cloud technologies.” In fact, it’s the single-biggest impediment to data governance success, according to these survey respondents. So the cloud is one of the biggest trends — and potential roadblocks — to data governance in 2022.

Keeping up with new data governance trends is possible when you have cutting-edge tools and resources in place. Learn about the Top data governance tools of 2022 here.

Disclosure: I work for MongoDB but the views expressed herein are mine.

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