Companies increasingly want to mature their Data Governance, the formal Data Management capabilities around its value as a service, in 2023. That way, organizations can respond to an uncertain business environment quickly and flexibly.
While Kelle O’Neal, founder and CEO of the data consulting firm First San Francisco Partners, first identified this need for Data Governance as a service in January 2022, a complex and voluminous data marketplace has made this approach imperative in 2023.
In current Data Governance attempts, many executives implemented a top-down oligarchical approach to deal with frustration with Data Quality, getting usable data from various projects. Data Governance based on this traditional approach fails to adapt to an increasingly digital environment.
Organizations will increasingly turn to a service-oriented bottom-up Data Governance program to achieve better Data Governance, like “how a human resources department” works. Organizations will evolve to a service model by combining the following:
- Adopting a dynamic Data Governance approach
- Empowering data stewards, enforcers of the effective control and use of data assets
- Improving Metadata Management, “the administration of data describing data within an organization emphasizing associations and lineage”
- Adapting to increasing data regulations
- Readying compliance with proposed AI regulations
Adopting a Dynamic Data Governance Approach in 2023
A dynamic Data Governance approach gives organizations flexibility when applying Data Governance directives to specific business scenarios. For example, if a company merges with another, it can scale up its Data Governance processes to handle more data access requests on demand.
Companies will want the right mix and match of processes and technologies to have the best dynamic Data Governance results. According to a 2021 Gartner Data and Analytics (D&A) governance survey, 61% of leaders indicated a desire to optimize data for business processes and productivity. Yet, only 42% believed they were on track to meet that goal.
In part, advancing technology will expand options with Data Governance operational efficiencies. The following advancing technologies will factor heavily:
- Cloud Computing: Cloud computing, technologies that store and access data on the internet, provide new capabilities to implement Data Governance directives while organizations monitor and analyze enterprise-wide data. For example, workers and systems will have nearly real-time access to datasets, as needed, while they work. This potential will increase the independence to make data-driven decisions adapting to frequent changes.
- Digital Twins: Digital twins enable a better understanding of the impacts of Data Governance policies because organizations can simulate different implementations in duplicated scenarios. This virtual functionality will allow companies to operationalize Data Governance to a plan ahead of time and adapt better than those who do Data Governance in response to a situation.
While companies have adopted a mix of cloud platforms and plan on implementing intercloud technologies to connect different cloud environments, only 6% of businesses in 2022 have leveraged digital twins. Prepare to see that number change. As companies migrate data to the cloud, they will require sophisticated technologies, like digital twins, to ensure the timely completion of Data Governance activities during the data movement.
Empowering Data Stewards
To get to a service model of Data Governance, organizations will focus on empowering data stewards, Data Governance monitors, and maintainers, implementing its policies in valuable ways. Data stewards handle daily decision-making based on Data Governance policies and present feedback from the workers on the ground to the Data Governance board.
Since cloud computing allows employees to work with data from anywhere, so data steward teams will become increasingly distributed. As more companies hire these remote or hybrid workers, organizations will modernize their data stewardship community building and technical supports.
Successful companies will offer Data Literacy training to empower and enhance data stewards from any location with first-hand shared data knowledge. A few businesses will follow American Fidelity Insurance’s CDO’s suggestion and host virtual internal data summits or events to inform other workers about how data stewardship contributes to the company’s profitability.
Simultaneously, organizations will invest in technologies that reduce their data stewardship workload and increase self-service among all workers. With investment in automated Data Governance platforms, data stewards will quickly serve up deliverables, like improved Data Quality during data migration.
Additionally, firms will tap AI and machine learning (ML) services, enabling data stewards to apply Data Governance solutions, such as changing the accessibility of datasets on demand. Also, ML and other automation will save data stewards time doing data profiling, surveying data values, and forming Data Quality.
Improving Metadata Management
As companies mature their Data Governance initiatives into a service model, they will improve their Metadata Management, the administration of data describing data within an organization emphasizing associations and lineage. Metadata Management, as O’Neal explains, advances businesses understanding of datasets found across it, including their contents, how to use them, and what constraints exist.
That benefit of knowing an organization’s data through metadata forms the backbone of Data Governance services, from Data Quality to regulatory compliance. For this reason, as Jelani Harper notes, “Metadata Management will likely always persist as the nucleus of Data Governance.”
The drive toward better Metadata Management to support Data Governance aligns with findings in DATAVERSITY®’s Trends in Data Management 2022 report. Many organizations have indicated, in the report, an emerging interest in metadata usage.
As companies continue to improve their Metadata Management, systems composing their data fabrics will add helpful information and metadata about processes with datasets. Consequently, organizations can mine any metadata logged passively to inform real-time use cases, such as applying Data Governance policies during data integration projects.
Adapting to Increasing Data Regulations
As firms adapt to increasing data regulations in 2023, they will have to take more of a Data Governance service approach. Analysts at Gartner have predicted that 65% of the world’s population in 2023 will be covered by laws similar to GDPR.
This reality means that as different stakeholders acquire datasets, they must comply with various data and privacy regulations. Given the amount of data and rules around that, companies that reframe Data Governance as a service will better adapt toward meeting data regulations.
In this service model, expect to see lawyers take a more significant role in Data Governance leadership and collaboration, helping companies understand different nuances. Only 17% have a committed Data Governance board with risk and legal professionals, which will likely grow in 2023.
Additionally, legislatures worldwide will continue expanding regulations around personal and other data types beyond ones like GDPRs. These laws will demand that organizations comply and keep up with rapid implementations.
To stay afloat in 2023, companies may outsource some Data Governance services, such as audits and employee training about regulations. As this happens, expect to see existing internal Data Governance roles evolve and change in 2023.
Readying Compliance with Proposed AI Regulations
Organizations will increasingly adopt a Data Governance service model as they increase implementations of AI technologies. The “EU and U.S. plan to impose new regulations to protect consumers and impact how algorithms can ingest, use, transform, and make recommendations based on datasets.
Companies have a short time to ramp up their Data Governance responses to AI because many algorithms adjust inputs and outputs in real time. Organizations need more Data Governance preparation, as only 30% of a McKinsey AI study respondents recognized potential legal risks as relevant.
The firms, blinded to the importance of AI regulations, will face increased pressure to adapt their Data Governance approaches by the end of 2023. EU’s draft AI regulations promise to impose more considerable fines on companies who fail to comply, 6% of their global revenue, instead of the 4% levied by the GDPR.
Consequently, worker adoption of Data Governance updates, in preparation for AI regulations, with their engagement and feedback, will play a crucial role in 2023. Furthermore, this preparation will encourage businesses to adopt a cloud Data Governance solution.
Conclusion
Data Governance will undergo a rapid maturation from a bureaucracy to a service. Firms will need to get everyone on board with this transformation, so supporting the data stewards on the ground will take on greater significance.
Firms will invest in automated Data Governance tools to handle service requests in real-time. These tools will leverage cloud computing and the virtual technologies behind digital twins.
Paramita Ghosh reinforces this trend towards technical investments by noting, “as more data flows to businesses, automated Data Governance (DG) processes will become high in demand.” In anticipation, the global Data Governance market size is expected to expand to “$7.42 billion in 2026 at a CAGR of 22.7%.”
In the past, companies made Data Governance decisions internally, as a bureaucracy, and had more control. In 2023 and beyond, decisions about Data Governance will shift outside the organization to regulators. Data Governance services will deliver solutions to achieve real-time business objectives by leveraging Metadata Management.
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