This article lists a few resources regarding Data Mesh. I will admit that this is a biased list of resources. I tried to strictly follow the lineage initiated by Zhamak Dehghani.
With every concept comes new words: this post illustrates some of the neologism brought by the Data Mesh paradigm. Let’s explore them.
After a (too long) hiatus, DataFriday is back. The first episode of the new season was released last Friday, January 14, 2022. It focuses on defining Enterprise Architects and how they are perceived and what they really bring to the enterprise.
I am an enterprise architect. Among the things I work on, I am bridging technology and business at the enterprise level. When I am on the technology side, I am talking to a lot of engineers and architects of various levels. When I am on the business side, I am trying to explain our technology constraints. That’s why I wanted to level-set vocabulary and concepts that I considered critical. I have cut the content into three twenty-minute videos available on YouTube.
Earlier this month, I was in San Francisco, CA, to attend Spark Summit 2017. I gave a talk on the phase before you can apply Machine Learning on data, using […]
Zaloni’s CEO Ben Sharma is speaking about managing data lakes. What has happened is IT department starts by installing Hadoop and jumps into Big Data. Not a lot of companies […]
When you start an application, you need to think about where it’s going to run, and also how it’s going to run. Basically, the way I use Spark is in […]
The Apache Software Foundation (ASF) offers a wide range of tools, libraries, frameworks, and data stores for building enterprise applications. The purpose of this list is to keep track of […]
People will start to believe that I am starting a series on agriculture (see my previous post: Name your fields, it’s easier when you’re gonna harvest). They would be partially […]