Code Breakfast June 24th - 8:30 -10:00 CET
Register here for the Code Breakfast
Register here for the Code Breakfast
Details
- Thursday, June 24th
- 8:30 – 10:00 CET
- Online
What to Expect
Build real-time views and dashboards on streams of data using Materialize and Metabase
Traditionally, performing real-time analytics on streams of data has been perceived as something hard that requires some skills that are difficult to find. You can build these skills yourself, of course, but imagine that you could do complex streaming analytics just writing a few lines of SQL and forget about Java or Scala.
That is what Materialize brings, an easy way to perform analytics on top of streams of data or continuously changing transactional databases. With Materialize, you can even combine streams of data in real-time, perform aggregations, and even publish your results to another topic to be consumed by a downstream service. In this real-time coding session, we will set up a local Materialize instance using Docker, subscribe to a stream of data and perform real-time analytics on it!
After that, we’ll be using Metabase, an open source data visualization tool, to display some real-time visuals on top of the Materialize views.
About the Speaker
Guillermo Sánchez Dionis
Guillermo is an Analytics Engineer with a really pragmatic and business oriented approach to Big Data Analytics.
He is a clear example of the evolution of the Data Analyst role towards a more engineering focused role powered by modern data platforms. His skills range from writing production-grade data pipelines to building data warehouses or modelling any type of data. He does this while bringing software engineering best practices into his work, which contributes to building scalable and resilient solutions.