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Unapologetically Technical Episode 10 – Michael Drogalis

Blog Summary: (AI Summaries by Summarizes)Interview with Michael Drogalis, founder and CEO of Shadow Traffic, discussing the early Hadoop era and the importance of Kafka

Why Most Data Projects Fail & How to Avoid It at GOTO 2023

Blog Summary: (AI Summaries by Summarizes)Data projects often fail due to similar reasons, with many management and data teams lacking understanding of project success factors.Understanding

Unapologetically Technical Episode 9 – Gunnar Morling

Blog Summary: (AI Summaries by Summarizes)Gunnar Morling, creator of the Billion Row Challenge and Senior Staff Software Engineer at Debezium, emphasizes the importance of staying

Unapologetically Technical Episode 8 – Tom Scott

Blog Summary: (AI Summaries by Summarizes)Tom Scott, Founder and CEO of Streambased, is interviewed in the latest episode of Unapologetically Technical.The discussion covers distributed systems

The State of Data Engineering at Data Day Texas 2024

Blog Summary: (AI Summaries by Summarizes)The premier of the latest talk covering The State of Data Engineering, discussing the industry’s history and future direction.The talk

Unapologetically Technical Episode 7 – Stephane Derosiaux

Blog Summary: (AI Summaries by Summarizes)New episode of Unapologetically Technical featuring an interview with Stephane Derosiaux from ConduktorDiscussion on evolving architectures and creating real-time systems

The Difference Between Learning and Doing

Blog Summary: (AI Summaries by Summarizes)Learning options trading involves data and programming but is not as technical as data engineering or software engineering.Different types of

Unapologetically Technical Episode 6 – Matteo Merli

Blog Summary: (AI Summaries by Summarizes)Matteo Merli, co-creator of Apache Pulsar and CTO of StreamNative, discusses the creation of Apache Pulsar and its significance.The reasons

The Data Discovery Team

Blog Summary: (AI Summaries by Summarizes)Data discovery team plays a crucial role in searching for data in the IT landscape.Data discovery team must make data

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