We’re creating more and more complicated data pipelines and systems with Kafka. These interactions are becoming even more complex as we create microservices. As we create these complex systems, we aren’t thinking about how to test, debug, or fix them....
Teams will often tell me how much better my training classes are than what they’ve had before. They go on to tell me how the training they’ve attended previously were useless. My students are surprised that I can answer programming questions, no matter how...
Sometimes I’ll write a post and the comments will say something to the effect of “this is useless.” Other times I’ll be finishing up a class and a student will ask me why I didn’t cover what they’re trying to. I’ve written...
In Chapter 3 of my Data Engineering Teams book, I show you how to do a skill gap analysis. During the analysis of the team, you either say the person has the skill or not. It’s a very binary decision. Some people have written me asking if it can be a fraction....
This post will focus on the key differences a Data Engineer or Architect needs to know between Apache Kafka and Amazon Kinesis. Cloud vs DIY Some of the contenders for Big Data messaging systems are Apache Kafka, Amazon Kinesis, and Google Cloud Pub/Sub (discussed in...
When a Big Data project fails, there’s plenty of blame to go around. When I do the retrospectives with teams who are failing or about to fail, their blame is often misplaced. There’s a focus on blaming the technology. The more difficult considerations of...
