Real-Time Business Analytics Using AI
Oct 31, 2023Zachary Hamilton
Summary
This post introduces the challenges and solutions for real-time business analytics using AI/ML, focusing on data quality and scalability. It highlights Confluent Cloud's capabilities in addressing these challenges through managed Kafka Connectors for data completeness, ksqlDB and Apache Flink for data context and transformation (including OpenAI API integration), and Schema Registry and Stream Governance for data consistency. The post also touches upon infrastructure scaling and continuous model training, positioning Confluent Cloud as a comprehensive platform for AI/ML-driven analytics.
More from the Real-time Enterprise RAG trail
- Building an Agentic SOC on a Stream
- Hemut: Building the Internet of Freight on Real-Time Data
- New in Confluent Intelligence and AI Tools: Making Agents Native to the Stream, Expanded Model Support, New Agent Skills, and Copilot
- Customer Intelligence Hub for Real-Time GTM Insights
- RAG and GenAI for Customer 360 Architecture