Through direct experience with data scientists, business analysts, lab technicians, as well as other UX professionals, I have found that we need a better understanding of the people who will be using our data visualization products in order to build them. Creating a product utilizing data with the goal of providing insight is fundamentally different from a typical user-centric web experience, although traditional UX process methods can help.
In this blog I will be demonstrating Kafka schema evolution with Java, Spring Boot and Protobuf. This app is for tutorial purposes, so there will be instances where a refactor could happen. I tried to […]
Redis is a popular open source in-memory data store that supports all kinds of abstract data structures. In this post and in an accompanying example Java project, I am going to explore two great use […]
First, let’s start with What is an AMI? An Amazon Machine Image (AMI) is a master image for the creation of virtual servers in an AWS environment. The machine images are like templates that are configured with […]