TDWI Checklist Report | Solving Data Engineering Challenges to Deliver Success with AI and Analytics
March 31, 2025
Data engineering is essential to achieving innovation in AI, analytics, and data-rich business applications.
Data engineers ensure that data is fit for today’s data-driven organizations. Data engineers collaborate with data scientists, software engineers, analysts, and business users to achieve cutting-edge objectives with machine learning, large language models (LLMs), generative AI, agentic AI, smart automation, and augmented BI.
It is critical for all organizations to solve data engineering challenges and deploy modern processes and technologies that increase scalability, efficiency, agility, and quality.
This TDWI Checklist Report discusses challenges and solution trends for future-proofing data engineering as organizations advance with AI and analytics and seek to support more users and workloads.