The Joe Reis Show
Freestyle Fridays - Shifting Left AND Right. The Data Engineering Lifecycle in 2025. What's Changed?
Mar 28, 2025
The conversation dives into the evolving perspectives on the data engineering lifecycle, highlighting insights from a recent conference. It emphasizes the need for collaboration between data engineers and source systems, especially in the age of AI. The discussion also explores how AI is revolutionizing data interactions and automating routine tasks. Additionally, it addresses the changing roles of data engineers as they adopt actionable workflows, uniting the fields of software engineering, AI, and data science.
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Quick takeaways
- Shifting left fosters closer collaboration between data engineers and source systems, improving data quality for analytics and machine learning.
- Shifting right introduces AI-driven interfaces that enhance interactions with data, allowing engineers to generate insights and automate actions effectively.
Deep dives
The Shift Left and Shift Right Paradigm
The conversation emphasizes the evolving landscape of data engineering through the concepts of 'shifting left' and 'shifting right.' Shifting left refers to the closer collaboration between data engineers and source systems, improving data quality for downstream applications like analytics and machine learning. Conversely, shifting right highlights new AI-driven interfaces that allow for innovative interactions with data beyond traditional methods. This dual approach not only enhances the effectiveness of data engineering but also positions data engineers to play a more significant role in actionable workflows that directly impact business outcomes.
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