Reading Update


Data Engineering

• What I learned from the open source data stack conference 2021 - A good recap on coalesce conference
• 7 Must-know Data Buzzwords - I know buzzwords can be something that goes as fast as it comes but I truly believe some of these are too stay (data mesh, metric store fo example)
• Iteratively Blog - Who should really own your tracking plan? - This isn’t very technical but it’s really important to know how to organize the products to make it possible to extract insights and data products ASAP
• Spark on Kubernetes in 2022 - As someone using AWS EMR for running Spark jobs, the usage of Kubernetes is quite a fresh of air and Joom makes clear the pros and cons of this approach
• Lightweight technology governance - This article can be a bit heavy but brings some good points on how automation and not locking the teams to a specific organization but give them enough advantages that they follow a common practice are great values I’d say any company should strive for
• Cost Efficiency @ Scale in Big Data File Format - Uber writes a great article on how a change of compaction method can lead to great down costs (in this case using ZTSD)

Engineering

• The Biggest Mistake I See Engineers Make - this article comes close to the heart as I tend to make these mistakes. Sure is a good reminder to go through fast iterations instead of falling into waterfall