There are two big problems with data governance today: one is data; the second is governance. No, I’m not trying to be cheeky. Data is a problem because every day it moves away from the comfortable row and column boundaries of relational databases. There is simply too much and a wide variety of data flowing through the enterprise at ever-increasing speed.
Data governance efforts can strive to tame these growing datasets, but too often governance policies and procedures fail. It can be comforting for a CIO to tell their CEO that they have a data governance team in place to bring security and process to a company’s data, but their company is still most likely among the 90% who says Gartner their data governance projects had failed.
However, all is not lost. In fact, current trends in data governance suggest that companies are learning from past failures and beginning to implement data governance that is less tool-centric and more people-centric, process-centric. Such processes will increasingly span the entire organization rather than remaining within an isolated team. But that’s not all that’s happening in the once stuffy world of data governance.
Data governance today
Data governance dictates how an organization manages its data throughout its lifecycle, from acquisition to disposal, as well as the different modes of use in between. Although data governance involves tools, it is much more than that: it also involves the processes people must follow to ensure data security, availability, and integrity.
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Traditionally, data governance was a highly centralized function that focused more on data control than innovation. This has changed, and in some organizations it has changed dramatically.
Due to “variable levels of uncertainty in today’s world”, argued Saul Judah, VP analyst at Gartner, data governance must embrace “speed and agility,” which has rendered “traditional approaches to data governance…obsolete.”
As such, modern data governance tends to be guided by principles that tie data to a business case so that the governance model can respond flexibly to business needs. Importantly, modern data governance never forgets the people involved, helping them protect and prepare data for enterprise use.
Top Data Governance Trends
It’s not just a matter of risk
Data governance has traditionally taken a top-down approach, identifying potential risks and attempting to block access to data. This was to ensure compliance with increasing regulatory requirements.
However, today’s data is gaining value through its use in machine learning algorithms and other revenue-generating activities, rendering old-fashioned data governance obsolete. Indeed, according to a Zaloni Survey 2022 of data governance professionals, the top two reasons for increased investment in data governance are data quality (74%) and analytics/BI (57%).
As Forrester has Underlineleading providers of data governance tools have “added collaboration features to bring data governance closer to where tribal knowledge and expertise lives.”
To make data more widely accessible, data governance tools are increasingly incorporating policy and stewardship management capabilities, simplifying access for a wider variety of user roles. Additionally, data governance tools often integrate AI/ML and related functionality from the outset.
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The goal is to democratize access to accurate and consistent data across the enterprise to facilitate business decisions. It is no longer about reducing data risk. Indeed, one of the big underlying trends here is increased data literacy efforts through organizations. While there are still steering committees and stewards to manage the data, the goal is to get the data safely into as many hands as possible.
From regulatory compliance to data quality
Data quality efforts are emerging as another big trend in the world of data governance. While it’s absolutely true that much of the recent interest in data governance has been driven by the proliferation of regulations, many organizations are looking at their more holistic data strategy to stay abreast of regulatory compliance. . During this shift, it has become even more critical for businesses to improve data quality. In fact, like the Zaloni survey revealedit is the main factor that motivates companies to take data governance seriously.
However, as Gartner has describe, improving data quality is more about process than tools. These processes include setting “good enough” standards for data quality and making it a recurring agenda item when the Data Governance Council meets. Such processes help ensure that employees can trust the data they use to power a range of operational use cases, but most importantly AI/ML With AI and ML technologies increasing awareness and cases business usage, consistency, integrity and overall data quality continue to drive business value.
The cloud changes everything
The reality of modern cloud computing underlies many of these changes. Although the cloud still represents a relatively small percentage of overall IT spending, it consumes a significant portion of net new IT spending. Directionally, this is where most IT spending is going.
Data governance appears in the cloud in two ways. First, more data governance tools now work in the cloud. Second, most of the data that requires governance policies comes from cloud-based applications.
As IDC has it predictedBy the end of 2022, more than 90% of enterprises globally will rely on a combination of on-premises/dedicated private clouds, multiple public clouds, and legacy platforms to meet their infrastructure needs.
It’s good and bad. This is good because it suggests that enterprises are taking data governance in hybrid architectures seriously. But it’s bad in that, as revealed in Zaloni survey data, few companies believe they have the “skills to manage new cloud technologies”. In fact, it’s the biggest barrier to successful data governance, according to survey respondents. The cloud is therefore one of the biggest trends – and potential obstacles – to data governance in 2022.
Keeping up with new trends in data governance is possible when you have state-of-the-art tools and resources. Check out the best data governance tools of 2022 here.
Disclosure: I work for MongoDB, but the opinions expressed here are my own.