Data has become a critical success factor for virtually every aspect of an organization’s strategic goals. Increasing pressure from competitive threats, supply chain and economic volatility, changing customer expectations, and more, combined with the foundational role data plays in digital transformation initiatives, create demand for ongoing real-time analytics from stakeholders across the enterprise.

At the same time, the data supply chain is constantly evolving with new systems, services, and apps, many of which are moving to the cloud to take advantage of elasticity and scale, while some data remains trapped in legacy systems.

This dynamic causes major data integration and delivery pains at the same time that data engineering talent is in short supply. But going with one of the common options — letting business users implement their own solutions, using cloud providers’ native data integration tools, or enforcing centralized systems and controls — can result in a complex, brittle, and costly architecture.

There is a better way.