Supernovas, Black Holes and Streaming Data

Sujitha — Fri, 16 Aug 2024 07:10:34 GMT

A Journey in Space With Apache Kafka and the Databricks Data Intelligence Platform

This blog post is a follow-up to the session From Supernovas to LLMs at Data + AI Summit 2024, where I demonstrated how anyone can consume and process publicly available NASA satellite data from Apache Kafka.

Unlike most Kafka demos, which are not easily reproducible or rely on simulated data, I will show how to analyze a live data stream from NASA's publicly accessible Gamma-ray Coordinates Network (GCN) which integrates data from supernovas and black holes coming from various satellites.

While it's possible to craft a solution using only open source Apache Spark™ and Apache Kafka, I will show the significant advantages of using the Databricks Data Intelligence Platform for this task. Also, the source code for both approaches will be provided.

The solution built on the Data Intelligence Platform leverages Delta Live Tables with serverless compute for data ingestion and transformation, Unity Catalog for data governance and metadata management, and the power of AI/BI Genie for natural language querying and visualization of the NASA data stream. The blog also showcases the power of Databricks Assistant for the generation of complex SQL transformations, debugging and documentation.

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Supernovas, Black Holes and Streaming Data