It influences successful action with the following characteristics:Īccording to Gartner, “data fabric requires substantial experience across multiple industries in the continuous use and reuse of data to discover, infer and propose data management infrastructure designs and to validate data objects.” Considering new and emerging architectures requires careful evaluation of the organization’s present data constructs. Data governance is a key enabler for data mesh and data fabric. At the same time, it needs to facilitate compliance with regulations, policies, standards and more.

Its overall value to the enterprise must incorporate the achievement of business goals. Limiting data governance to a narrowly defined objective of compliance is short-sided. Data Governance as an Enablerĭata governance is critical in enabling enterprises to successfully adapt to changing business and regulatory environments. It requires clear identification of stakeholders, empowerment, recognition and rewards. Getting the “right” people to do the “right” thing with the “right” data is not always easy. This enables companies to fully exploit their accountable data resources.

One goal of data fabric is to democratize - or improve understanding for all. Stewardship sits at the heart of data mesh implementations.

It also places proper custodianship for a company’s data with people closest to the data. It's a requirement to drive successful data mesh and data fabric architectures.Īs stated in the earlier blogs, data stewardship is a core tenet of suitable data governance. In this blog, I will present data governance as an imperative. In the second blog, I compared data mesh and data fabric based on three factors: accountability of people, methodology of process and technology used. In the first blog of this three-part series, I explained how to associate data governance with data mesh and data fabric architectures.

Mesh enabler