Beyond Pipelines

Chapter 1. The Hidden Cost of Fragmented Data: A Barrier to Agentic Transformation

For years, organizations have approached their data and application projects by having two distinct teams work in parallel, using their own specialized skills, tools, and goals. Data teams consist of data engineers and analysts who build pipelines to centralize and integrate data into a central data warehouse or lakehouse. In this way, data can be transformed into insights. Integration teams, on the other hand, consist of IT application engineers and developers who enable application-to-application business process automation.

The idea that these teams should work separately evolved largely around the availability of specialized tools—distinct platforms for data warehousing, extract-transform-load (ETL), and application integration that required different technical skills. Today’s unified platforms bring these functionalities together, but organizational models lag behind the technological capabilities.

Today we are witnessing intelligent systems that can take action, make decisions, and automate workflows across systems and business operations, and these systems are fundamentally rewriting the rulebook. They don’t stop at offering recommendations—they execute them. And to operate effectively, they require something most organizations simply don’t have: unified, consistent, high-quality data that flows seamlessly across the entire enterprise.

The Limits of Disconnected Data

Businesses are drowning ...