Series

AI-AUGMENTED DATA ENGINEERING

Modern data platforms have outpaced our ability to see them clearly. This series explores how AI restores that clarity — across data quality, observability, root cause analysis, metadata intelligence, and cost optimisation. Written for engineers who build and leads who decide, each article pairs implementation depth with an honest reckoning of risk. The lens is Advaita: viveka — discriminative discernment — applied to the hardest problems in data engineering.

The Case for AI in Data Engineering
Series: AI-Augmented Data Engineering | Article 1 of 7 There is a quiet crisis in most data engineering teams. Pipelines fail at 2 AM. The on-call engineer spends three hours tracing a root cause tha
May 31, 20267 min read15
AI-Driven Data Quality: From Rules to Reasoning
AI-Augmented Data Engineering | Article 2 of 7 | tech4nirvana.com
Jun 20, 202611 min read21
Observability That Thinks: AI for Pipeline Monitoring
AI-Augmented Data Engineering — Article 3 of 7
Jul 30, 20268 min read15

Command Palette