The data analysis landscape is on the precipice of a paradigm shift. Generative AI (GenAI) promises revolutionary insights, but traditional systems struggle to feed its insatiable appetite for well-structured data. Imagine GenAI as a high-powered engine – it needs meticulously organised fuel to reach its full potential.
In this episode of the EM360 Podcast, Analyst Christina Stathopoulos guides Deborah Leff (CRO at SQream) and Jason Hardy (CTO, AI at Hitachi Vantara) as they dissect:
- The Bottlenecks of Traditional Systems
- Unlocking GPU Potential
- Fueling Insights with Structured Data
- Faster Time to Insights
This episode goes beyond theory, exploring real-world examples (like a company querying a staggering 64 quadrillion rows) It showcases the potential for SQream and Hitachi Vantara to empower organisations to make data-driven decisions with unprecedented speed and accuracy.
SQream is a company specializing in data processing and analytics acceleration, utilizing a unique GPU-patented SQL engine. It provides solutions for organizations that need to analyze massive amounts of data, ranging from terabytes to petabytes. The company's focus is on delivering high-performance, cost-effective data management and analytics platforms, tailored for handling large and complex datasets with speed and efficiency.
Comments ( 3 )