AI initiatives are scaling, and so are the costs tied to data infrastructure.
According to a new study by Nucleus Research, organizations implementing open lakehouse architectures are reporting:
- 60%–70% improvements in ingestion processing costs
- 25%–30% reductions in query compute costs
- Up to 5X faster processing performance
- Significant reductions in platform management effort
In this Qlik Insider session, host Dan Potter is joined by Tim Garrod and Nucleus Research analyst Alexander Wurm to examine the findings behind The Value of Qlik Open Lakehouse.
You’ll get a practical understanding of:
- Where measurable ROI is being realized
- How automation reduces operational overhead
- Why open formats like Apache Iceberg matter for long-term flexibility
- What to evaluate when modernizing your data architecture
Register for a research-driven discussion on building a cost-efficient, AI-ready data foundation.
Register here