This white paper highlights how data engineering is central to unlocking the value of advanced analytics. While organizations face challenges with data quality, integration, and scaling, data engineering provides the foundation for reliable insights. It builds pipelines that unify data, reduce errors, and accelerate AI/ML projects by ensuring trusted, well-governed datasets. The paper stresses that data engineering is not interchangeable with software development; it requires specialized skills in architecture, data governance, and toolchains. By integrating DataOps, businesses can overcome silos, automate workflows, and scale analytics efficiently.

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