Organizations want Data Governance, a formalized practice that connects different components – roles, processes, communications, metrics, and tools – for its benefits. Company-wide data represents a resource that will “become more valuable than people ever anticipated,” according to David McGraw, senior manager in consumer and industrial products at West Monroe.

Advances in generative AI models in 2023 will only increase the popularity and importance of well-governed data and its advantages so data consumers can easily find and understand data. Not only will this kind of information help businesses improve and grow through AI’s augmentation, but customers will be able to use it to support training their AI models and product creations.

Yet, while many understand Data Governance has benefits, getting effective Data Governance has proven elusive due to excessive bureaucracy. Gartner estimates that through 2025, 80% of organizations seeking to scale digital business will fail because they must take a modern approach to Data Governance, including a service model.

As companies evolve to include service models in their Data Governance, benefits will become more apparent, including:

• Establishing data ethics, a code of behavior that creates a trustworthy and fair business climate
• Ensuring Data Quality, good business fitness of the data
• Enabling smoother corporate-wide communications
• Empowering decision-making
• Expanding Data Governance’s benefits

This article covers each of these advantages below.

Establishing Good Data Ethics

An adaptable Data Governance program with good service establishes a company capable of managing its data because of data ethics. The positive results become apparent when a company knows how it uses and keeps the data it produces, why it needs it, and who can access it. 

Since 2018, starting with the European General Data Protection Regulation (GDPR), various jurisdictions have enacted laws to protect consumers’ privacy and require companies to comply with audits. Further expanding legislation will add nuances and cover 65% of the world’s population, demanding that Data Governance keep current with its services to more data consumers.

Consequently, enterprises view Data Governance as a must-have program to reduce risks and costs and to stay compliant. However, only successful, routinely implemented Data Governance processes provide documented evidence demonstrating compliance.

While data laws set the limits of socially acceptable activities with data, data ethics also encompasses civic responsibility that positively impacts people’s lives. Therefore, Data Governance programs must address current data ethics challenges visibly and consistently to receive greater rewards through established business growth.

Ensuring Data Quality

Without a doubt, Data Quality and the planning, implementation, and control of activities done to ensure it is fit for consumption hovers at the top of Data Governance benefits. Fortunately, good Data Governance services get better Data Quality through:

• Metadata management: Data Governance facilitates a better understanding of what data exists, where it comes from and when, and how it is used through metadata management, a collection of policies, procedures, and systems that are used to administer data that describe other data. Think of metadata management as the nucleus of Data Governance that persists. Adaptable Data Governance scans ingested data and data processing for changes in content and context and enables systems, processes, or people to update or create new metadata. In addition, this Data Governance service supports active metadata management – tasks that align Data Quality to reality and account for exceptions.

• Automation and artificial intelligence (AI): Automation to ensure Data Quality has improved significantly through Data Governance platforms. AI allows organizations to discover and classify data quickly, in near real time. Furthermore, algorithms can quickly identify Data Quality problems by looking at deviations from expected values. Machine learning also makes suggestions that improve standardization and consistency, revealing data sets for easier searching.

• Data stewardship: Having the right people oversee data through formalized stewardship roles enhances Data Quality. Data stewards, typically experts in a domain, take responsibility for processes that ensure effective control of data assets, contributing to that domain’s Data Quality. As business shift their hiring models and adapt to a turbulent marketplace, expect to see data steward personnel change frequently. So, companies will benefit from technologies increasing self-service among data stewards and reducing their workloads through AI and machine learning.

Enabling Smoother Corporate-Wide Communications

Before Data Governance benefited corporate-wide communications, different groups would frame and talk about data differently, causing problems down the road. For example, Donna Burbank, managing director of Global Data Strategy, has shown a cartoon where a group is finished technically constructing an application but needs to know how to define a customer.

This type of miscommunication keeps coming up in newer technologies. For example, teams may define jobs that transform this data differently when processing big data sets. 

Through Data Governance with a service, different corporate sections resolve data definition disputes and achieve alignment when conceptualizing what data means and how to use it. The shared journey and accountability across roles set a starting point for building organizational Data Literacy, the ability to read, write, and communicate about data in the business context.

Consequently, corporations end up standardizing terms so that the technical and business teams are more precise about what they build together. This unification results in deliverables such as business glossaries (internal vocabulary terms), knowledge graphs (ontologies with terms and relationships), or data catalogs (data inventories) that work to facilitate corporate-wide communications and act as living resources to keep conversations current and on the same page.

Empowering Decision-Making

Companies with good Data Governance services benefit from more comprehensive support to leaders, workers, and automated systems, empowering their decision-making. In addition, consistent and uniform data policies and processes lead to increased trust in data, benefiting data-driven decision-making. 

A formalized control of the entire corporate body of data gives leaders a complete picture of business activities, challenges, and opportunities. In addition, with Data Governance of streaming and unstructured data, executives can respond quickly for the best outcome – such as redirecting shipments when a region experiences sudden flooding.

Some business decisions must be handled locally at the ground level and need a faster response than a manager can give. For example, a truck driver may receive notification of a severe weather event and needs to choose an alternate route. They may use timely data from Data Governance when deciding on a detour.

In 2023 and beyond, companies will see a tremendous rise in their automation of business processes through AI and machine learning. However, for these applications to assist with decision-making, they must be trained with good-quality and timely data, both benefits of good Data Governance.

Expanding Data Governance’s Benefits

As more people see the value of Data Governance, its benefits will expand to other communities, such as those working with new technologies. Furthermore, these good Data Governance practices will make company mergers or acquisitions more manageable. 

Ideally, the trusted data services provided through corporate Data Governance benefit the larger environment and societies where the business functions. As Dan Wu et al. stated in a Cambridge University Press article:

“With new data-sharing arrangements, less-resourced innovators — including individual researchers, citizen developers, local communities, and small and medium-sized enterprises— can access sufficient data to fuel artificial intelligence and data analytics, reframe problems, and solve them in new ways.”

In this way, Data Governance promises a greater data democratization, a methodological framework of values and actions that benefit and minimize any harm to the public or the typical user. In addition, data democratization opens the door to human resources beyond data scientists, offering new perspectives and leveraging members in different disciplines.

Conclusion

Good Data Governance, which uses a service model, promises many benefits within and outside organizations. These advantages include data ethics, Data Quality, smoother corporate-wide communications, empowered decision-making, and expanded communities that can handle data better. 

These capabilities mean that data consumers of different origins can quickly gather and compile multi-structured data from disparate sources and then convert their data into appropriate responses that impact companies and communities positively. Good Data Governance promises this kind of future – an ideal that resonates with many people.

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