From Data Engineering on Azure by Vlad Riscutia
This article talks about building identity keyrings
From Privacy by Design by Nishant Bhajaria
This article series explores incorporating privacy into your design from the beginning using automation.
From Privacy Engineering by Nishant Bhajaria This article series explores incorporating privacy into your design from the beginning using automation. Take 40% off Privacy Engineering by entering fccbhajaria into the discount code box at checkout at manning.com. See part 1… Continue Reading →
From Software Telemetry by Jamie Riedesel
This article covers emitting and shipping telemetry to somewhere off the system, such as into a queue.
In this video, Billy, Alexander, Todd, and Jesse explain key concepts and walk you through demos of GitOps and Kubernetes.
In this video, Ashley Davis demonstrates how to upgrade your infrastructure through code using Terraform.
In this video, seasoned IT professional Richard Nuckolls dives into writing and running Azure Data Lake Analytics jobs.
By Vlad Riscutia
This is an excerpt from chapter 2 of my book — Data Engineering on Azure — which deals with storage. In this article we’ll look at a few aspects of data ingestion: frequency and load type, and how we can handle corrupted data. We’ll use Azure Data Explorer as the storage solution, but keep in mind that the same concepts apply regardless of the data fabric used. Code samples are omitted from this article, but are available in the book. Let’s start by looking at the frequency with which we ingest data.
