Convert batch data into streaming with Python

Presented by: Bobur Umurzokov

The advent of real-time data processing has redefined how businesses operate, but the journey to real-time has its challenges. Many organizations find themselves juggling separate workflows and teams for batch and streaming data processing, each presenting unique difficulties. Batch processing, while effective for large datasets, can be costly, slow, and not well-suited for API integration. On the other hand, streaming, despite its speed and low latency, often has restricted functionality.

This talk explores how Pathway is an open framework in Python for real-time data processing that provides a unified platform for batch and streaming. You will see with examples how simple it is to make your batch code run in streaming and learn how to build a data processing pipeline that ingests data from various data sources, processes, analyzes, and sends it to output streams in real-time.

Tags: Backend, Data Science, DatabasesLevel: Intermediate