Redefining Data Governance: Bridging The Gap Between Technical And Domain Experts

Tim Ward is CEO of CluedIn. He is passionate about making data work for everyone. In the ever evolving landscape of data management and utilization, it's crucial to address the prevailing myth that data governance and master data management (MDM) are disciplines strictly reserved for those with technical expertise.

As someone deeply rooted in the technical sphere, I have always resonated with my fellow tech professionals. Yet, there's an overlooked aspect in the field of data: The potential contributions of non technical domain experts are often underappreciated and underutilized in the data supply chain.

The core of this issue revolves around the concept of "persona." IT and engineering departments have historically been the backbone of data infrastructure, playing a pivotal role in its architecture and maintenance. This has fostered a belief that the realms of data governance and MDM are best left to those who can "code" solutions.

However, this perspective overlooks the nuanced challenges that are beyond the scope of automation and technological fixes. The Current State Of Data Governance Year after year, companies chase the latest technological innovations, yet they drift further from addressing systemic data management issues that require the insight and expertise of domain experts.

These domain experts, often sidelined due to their lack of technical expertise, hold invaluable knowledge about the data itself. Their role has been traditionally confined to that of data "consumers" in the era of self service. We are transitioning, however, into a period where these experts will emerge as "producers" of company wide data, a role significantly different from their previous contributions.

While domain experts have always been involved in data production at an operational level through systems like ERP and CRM, their influence on the overarching company data narrative has been minimal. Consider a common scenario in many organizations: managing customer data across multiple systems. The fragmentation of customer data necessitates an integration point, a juncture where various data streams converge for purposes like reporting, RPA, AI and invoicing.

While data warehouses and data lakes have played a part in this process, they have been predominantly IT and engineering centric, overlooking the critical input of domain experts. These experts are the ones who can discern conflicting data records and make informed decisions on data accuracy and integrity, influencing both downstream and upstream systems.

Empowering Domain Experts As the data industry gravitates toward decentralization, specifically federated systems, the absence of a robust framework in data governance, master data and data quality becomes glaringly evident. The prevailing issue in many companies is not the sheer volume of data or a lack of technological options but the erroneous assumption that their data is inherently primed for insights, AI applications and democratization.

This misconception overshadows the real challenge: the need for a comprehensive approach to data management that integrates the expertise of domain professionals. The advent of practical AI applications marks a watershed moment in the history of data governance. This technology is not just a tool for automation; it serves as a bridge between the technical and business realms.

It provides a platform where business experts can meaningfully contribute to data strategies and decision making processes. Technical teams initially assumed the mantle of data governance out of necessity due to the requisite skill sets. However, this landscape is undergoing a transformative change.

We stand on the brink of an exciting era where data governance will gain momentum, propelled by a collaborative approach that involves both technical and domain experts. Companies can foster collaboration between IT and business units and empower and enable domain experts in data management and data governance by implementing several key strategies.

1. Establish a unified vision. Alignment starts with a shared understanding of goals. Both IT and business teams should be involved in setting the objectives for data management and governance. This collaborative process ensures that the data strategy supports both technical and business needs. 2. Create cross functional teams.

Teams that include members from IT, business units and data governance can foster collaboration and work on specific data projects, ensuring that all aspects of data management and governance are considered from both a technical and business perspective. 3. Identify responsibilities. Make it abundantly clear that the goal of domain experts is to be the owners of the actual end data product and that IT will play a significant role in the delivery and infrastructure for this, but that the domain experts are the ones charged with improving and enriching the data itself.

Conclusion Looking into 2024 and beyond, the emphasis on data governance will become increasingly vital for every data leader, practitioner and organizational leader. The untapped potential within data governance is enormous, poised to unleash significant ROI and unlock the full capabilities of AI. Data governance is more than just an IT initiative; it’s a strategic business endeavor that is key to democratizing data and driving innovation.

The future of data management and governance is an inclusive one, where the insights and expertise of both technical and domain experts are equally valued and integrated. By embracing this collaborative approach, organizations can not only solve current data challenges but also pave the way for future advancements in AI and data democratization.

The redefinition of data governance from a purely technical discipline to a collaborative, cross functional field is not just a necessity but an opportunity to unlock new levels of efficiency, innovation and value creation in the realm of data. Forbes Technology Council is an invitation only community for world class CIOs, CTOs and technology executives.

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