As organizations increasingly embrace artificial intelligence (AI) to unlock new opportunities, many face significant challenges in managing the massive data volumes required to fuel AI success. Scaling, cost management, and performance issues are just the tip of the iceberg. The real challenge? Effectively storing, managing, and leveraging both historical and real-time data to build AI models that deliver true value. Without a comprehensive data strategy, your AI initiatives could fall short of expectations.
To help you overcome these challenges, this whitepaper from Quantum explores the essential components of an AI-optimized data infrastructure.
Read this whitepaper to learn:
- The critical role of data storage in driving AI success
- Strategies to overcome common AI challenges such as scalability, performance, and cost management
- Effective methods for managing growing data volumes, from real-time "hot" data to expansive historical data lakes
- Insights into optimizing AI performance and sustainability through tiered storage and hybrid cloud deployments