(R)EVOLUTION OF DATA ENGINEERING: The journey towards auto-engineering

What's Inside This Whitepaper: The (R) Evolution of Data Engineering

Rethinking Data Pipelines for Speed and Scale

Discover why traditional, manual data engineering approaches can no longer meet today’s business demands. Learn how automation and AI are redefining how data pipelines are built, deployed, and governed.

The Rise of Auto-Engineering

Explore the concept of auto-engineering—a pragmatic, system-level approach that accelerates pipeline delivery without sacrificing control or quality. Learn how modern frameworks like dbt, combined with Infrastructure-as-Code practices and business manifests, enable faster, more scalable, and governed data development.

Building Your Data Pipeline Factory

Understand how organisations are moving away from bespoke, one-off pipelines towards a repeatable, governed “pipeline factory” model. Get insights into Keyrus’ proven framework that blends automation, governance, and business alignment.

Governance and Trust in Automated Systems

Learn why governance remains critical—even in an automated environment. The whitepaper outlines how to embed data quality, lineage tracking, and regulatory compliance into your pipeline automation processes from day one.

Delivering Tangible Business Value

See how modern data engineering practices can reduce total cost of ownership (TCO), improve time-to-insight, and empower both business users and technical teams to work more collaboratively and effectively.

Download this FREE e-book to discover how automation and AI can help you scale, govern, and accelerate your data engineering processes—while reducing cost and complexity.