You Can’t Have Data Mesh Without Governance
Create a Data-Driven Culture
As the volume of big data keeps growing, traditional tools used to manage it can fall short. Demand for data science led many organizations to try combining their data warehouses with big data tools. The challenge is that trying to deploy data this way can cause huge backlogs, especially in large organizations. If a single team owns both the data platform and all integrations, other teams that need analytics can lose time while they wait for their results.
Even if the data team owns all infrastructure, the volume of data they work with is often larger than what many business intelligence (BI) tools can handle. The number of data sources is often numerous as well. This situation makes a strong case for not having one team manage all data in one platform. Unless your organization is small, this option is bound to cause silos, backlogs, and lost productivity.
Using data mesh — an architectural pattern that lets cross-functional teams manage data domains as products — can ease these risks.
