Bring Your Own Stream: Deploying Algorithms Closer to Data for Real-Time Analysis

MEET THE HOSTS: Nima Negahban – Founder & CTO – Kinetica, Tim Barr – Director, Federal Solution Engineering – Kinetica

The growth of streaming data sources is driving the need for real-time geospatial, graph analytics, and machine learning capabilities at scale. These high velocity use cases require a streaming data warehouse, a platform delivering up-to-the-second analysis on data as it arrives. Learn why legacy systems won’t hold up and why the Kinetica Streaming Data Warehouse is suited for real-time analysis and high-velocity, high-scale use cases.

DURING THIS WEBINAR WE WILL COVER:

• Best practices for developing a system architecture for a streaming data warehouse
• Integrated model training with NVIDIA RAPIDS
• Autonomous Kubernetes orchestration
• Comprehensive model auditing
• Accelerated geospatial and graph analytics at scale using the raw processing power of the NVIDIA GPU
• Example implementations from our work with federal clients, including the Department of State and the U.S. Postal Service, where we optimize routes in real-time for carriers and 250,000+ vehicles