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Stream, Store, Visualize: Fast-track Real-Time Analytics the OSS Way
Originally aired:
About the Session
Many developers struggle with the complexity of setting up streaming analytics—wrestling with configurations, compatibility issues, and integration challenges. However, choosing the right open-source tools can drastically reduce setup time, enabling real-time analytics pipelines in minutes, not weeks.
This session features a live demonstration of building a complete streaming pipeline on a laptop, using Apache Iceberg for storage and Streamlit for real-time visualization. Attendees will gain hands-on experience in integrating data sources, configuring storage, and creating dashboards, all within a local development setup that mirrors production architecture.
Key Takeaways
- Configure a local streaming development environment.
- Integrate various data sources and sinks efficiently.
- Implement Apache Iceberg for scalable data storage.
- Build real-time dashboards using Streamlit.
- Understand production deployment patterns for real-time analytics.
Target Audience
This session is ideal for data engineers, software developers, and AI practitioners who want to build real-time analytics pipelines using open-source technologies. It is also valuable for architects and DevOps engineers interested in optimizing data infrastructure for low-latency, high-throughput analytics.
Prerequisites: Basic knowledge of SQL and Python.
Stream, Store, Visualize: Fast-track Real-Time Analytics the OSS Way
Originally aired:
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