Better Together: Data Management, Data Integration, Data Quality, and Data Governance

As we move into a modern era of data management, organizations are beginning to look at effectively managing smaller, distributed data sets with data integration, quality, and governance that are accurate, faster, and—perhaps most importantly—oriented to their data consumers.

Master Data Management Knot Data Hubs

Toward a Modern Data Management

Traditional enterprise master data management (MDM) projects have long suffered the challenge of coming up with a single source of truth definition that applies to data from the enterprise level for operational systems down through to granular, functional use cases at the local level. Now, with the advent of data hubs organizations are also establishing agreement on data definitions among smaller groups of subject matter experts, achieving higher quality and highly governed data intended to serve subsets of the company without chasing a single, elusive one-size-fits-all agreed upon definition.

This isn’t to say that the data hub can’t be used for the enterprise—it can—but simply that leveraging data hubs to service smaller groups within the enterprise circumvents the pain point of trying to have everyone in the organization agree on one thing. Instead, this approach creates a tapestry of governed, quality data hubs that allows for flexibility and compromise where needed, facilitating the two most important factors for today’s data-driven organizations: speed and agility.

A New Era of Data Culture

This adjustment from enterprise-wide to purpose-specific semantic definitions is part of a transformation driving a new era of data culture. The central theme here is context, both in the context of the data’s definition and its use throughout the enterprise.

Consider the concept of tribal knowledge and how it relates to how we think about the semantic context of data. Tribal knowledge refers to information known within a tribe; the collective wisdom of the organization, the sum of knowledge and capabilities of its people. As an overarching nation, an organization is made up of many tribes, each with their own dialect, way of doing things, mindset, and, of course, context. In each of these tribes, data definitions can vary and be used in ways specific to the needs of the tribe, or business unit.

Having a tribe agree on things is much easier, and faster, than having a nation agree. In this way, MDM still needs to have shared definitions and identities with other tribes—to build a culture across the enterprise. A multi-domain data platform gives all the enterprise’s tribes one place to work within a unified sphere, but remains true to their own individual needs.

The future of data management, we believe, will find organizations embracing the more agile and highly governed benefits from tackling smaller subsets of data context with data hubs as part of an overall enterprise data management strategy. This is where data integration, quality, and governance come together to enable the organization to derive the most value from the tribal knowledge of its business units, delivering speed, agile, and insightful decision-making across the enterprise. We have been observing these changes and trends at clients and in the industry over the past several years and we look forward to sharing our research with you in a future Radiant Advisors’ Insight Paper.