AI Data Blog and Insights

Modern Data Engineering extends far beyond building pipelines. Part 9 of the Info2K Data Engineering for AI series explores how data quality, governance, context engineering, observability and connected DataOps, MLOps and GenAIOps practices provide the foundation for reliable enterprise AI.

Cloud services alone do not create an AI-ready data platform. Part 8 of the Info2K Data Engineering for AI series explores how ingestion, processing, governance, security, observability and trusted data products work together to support reliable AI at scale.

ETL or ELT: which approach is better for modern AI systems? Explore where data transformation should happen, the strengths and risks of each pattern, and why hybrid architectures often provide the right balance between governance, flexibility, and scale.