On Thursday, 28 February 2019, I’ll be teaching a brand-new course from Microsoft called “Microsoft SQL Server Big Data Clusters … More
Category: Data Science, Artificial Intelligence and Advanced Analytics Project Management
Syllabuck: Ignite 2018 Conference
(A “Syllabuck” is like a Syllabus, but more like that second definition, and certainly more random) I recently attended, presented, … More
DevOps for Data Science – Load Testing and Auto-Scale
In this series on DevOps for Data Science, I’ve explained the concept of a DevOps “Maturity Model” – a list … More
DevOps for Data Science – Application Performance Monitoring
In this series on DevOps for Data Science, I’ve explained the concept of a DevOps “Maturity Model” – a list … More
DevOps for Data Science – Continuous Delivery
In this series on DevOps for Data Science, I’ve explained the concept of a DevOps “Maturity Model” – a list … More
DevOps for Data Science – Continuous Integration
In the previous post in this series on DevOps for Data Science, I covered the first the concept in a … More
DevOps for Data Science – Infrastructure as Code
In the previous post in this series on DevOps for Data Science, I explained that it’s often difficult to try … More
DevOps for Data Science – DevOps Maturity
In this series on DevOps for Data Science, I explained what DevOps is, and given you lots of resources to go … More
DevOps for Data Science – Defining DevOps
I’m wading into treacherous waters here in my series on DevOps for Data Science. Computing terms often defy explanation, especially … More
The Keys to Effective Data Science Projects – Part 9: Testing and Validation
We’re continuing our discussion of the series of the Keys to Effective Data Science Projects, this time focusing on Testing and Validating … More
