Data Summit 2023 delivered a candid snapshot of where enterprise data management actually stands — beyond vendor keynotes. The dominant threads: generative AI's collision with data governance, the pragmatic rise of data mesh thinking, and the unglamorous but urgent work of data quality.
Trends we tracked
Sessions repeatedly returned to a handful of themes that mirror what we see in client engagements.
- LLMs are only as trustworthy as the data pipelines feeding them — retrieval quality is a data-engineering problem.
- Data contracts and domain ownership are moving from conference slides into real org charts.
- Streaming-first architectures are becoming the default for operational analytics.
- Observability for data (freshness, drift, lineage) is now a budgeted line item.
The gap between data leaders and laggards is widening. The good news: proven reference architectures make catching up faster than ever — and that is precisely the work our data engineering team does every day.