Video recording of a joint webinar on November 14th 2017 by Rupal Shah from Streamsets and Audrey Egan from MapR. "Machine learning (ML) and artificial intelligence (AI) enable intelligent processes that can autonomously make decisions in real-time. The real challenge for effective ML and AI is getting all relevant data to a converged data platform in real-time, where it can be processed using modern technologies and integrated into any downstream systems.
Running a business in real-time means being able to react to important business events as they happen. Applications that support day-to-day operations, however, are often scattered across the organization making it difficult to enable real-time movement of data.
In this session, MapR and StreamSets will discuss how change data capture (CDC) can be used to enable real-time workloads to drive success with ML and AI. You’ll see live demonstrations of technologies that enable CDC, and specifically learn how to:
- Utilize change data capture (CDC) for efficient real-time data movement & processing
- Connect your databases, data warehouses, and data lakes without code
- Use MapR-DB as both source and destination for change data capture"