Machine Learning on Databricks for Data Engineers
A data engineer's walkthrough of two end-to-end ML pipelines on Databricks : load, clean, train, save and score using Spark, tables and a little Python.

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Articles tagged with #azure
A data engineer's walkthrough of two end-to-end ML pipelines on Databricks : load, clean, train, save and score using Spark, tables and a little Python.

💡 TL;DR: This article presents a complementary approach to Power BI deployments using blue-green deployment strategies with Docker containers, by leveraging existing classic Power BI deployment pipelines along with Azure DevOps pipelines, Fabric CLI...

Code-First and Low-Code: Tailored Solutions Explained

Picture this : you've got valuable data locked away in Microsoft Fabric, perfectly organized and secure. But now you need to share that data with external applications, power dynamic dashboards, or integrate with third-party tools. The question that ...

Have you encountered a situation where a Power BI report seems stuck in time, with slicers for eg: month failing to reflect the latest data? It’s a common frustration - users continue to see outdated selections, even though newer entries have arrived...

A month ago, I promised on my previous LinkedIn post that I'd show you how to track YouTube live streams from Sri Lanka's prime-time news channels using the Real-Time Intelligence (RTI) capabilities in Microsoft Fabric — and here we are. This blog ta...
