Real-Time Predictions with Machine Learning & Redpanda Streaming Data Transforms

Welcome to another iteration of Data Engineering Boston Meetup.

In this session, we will demonstrate how to avoid common pitfalls associated with complex data structures and data stacks, and will gain insights into creating more effective, agile, and responsive applications – especially for AI. The methodologies are applicable across various industries and use cases.

We'll cover the creation of an efficient data platform using Redpanda data transforms powered by WebAssembly (WASM), particularly tailored for dynamic industries (we will use food delivery as an example). We'll show how to simplify your data stack and demonstrate with a lab how complex data structures often hinder the agility and performance of AI systems. The lab will focus on stateless pipelines, where each data item is processed independently, and showcases how to build scalable and robust AI applications without the burden of cumbersome data frameworks.

The following tech topics will be covered:
• Streamlined data ingestion and transformation
• Real-time machine learning
• Simplified infrastructure setup

Agenda below:
(Note - At this point, this is a in-person Meetup only)

5:30-6:00pm: Arrivals, Networking, Food
6:00-7.00pm: Presentation and Q&A
7:00pm - 7.15pm: Follow up & Wrap up