Session Abstract

In this talk, we’ll explain what is Data Observability and how it can help data teams detect and stop incident propagation by tracking and measuring data usage across systems, projects, and applications in real-time. We’ll also see how it helps organizations efficiently improve dynamics between teams, increase confidence in analytics, and even take part in the Data Mesh architecture.

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Speaker

Andy Petrella, Founder Kensu

Bio

Andy is an entrepreneur with a Mathematics and Distributed Data background.

Andy is known as an early evangelist of Apache Spark and the Spark Notebook creator in the data community. He is also an O’Reilly author “What is Data Observability”, “What is Data Governance”, and trainer “Distributed Data Science”, “Data Lineage Essentials”, “Machine Learning Model Monitoring”.

Andy is also the founder and CEO of Kensu.io, a data observability solution implementing the Data Observability Driven Development (DODD) method.

Social media links

How did you originally get involved with data architecture and / or data engineering

I fell into the cauldron almost since day one after uni.

After I started in GIS, in worldwide projects dealing with huge geospatial data on legacy systems. After that, I started a career in big data and distributed AI in Europe with the Spark Notebook, which lead me to work in the Valley for 3 years. Finally, Kensu.

What one data architecture or data engineering book would you take to a desert island. Please give a brief description of the book, and why it stands out.

Geez… recently, either Data Mesh or Fundamentals of DE.
Otherwise, I’ll go with the classic “Designing Data-Intensive Applications

But if I had to read again and again and again one book, I’d go with the DM one to ensure enough room for creativity and abstraction before I switch to a volley ball

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