Neal News: A real-world approach to AI and MLOps

Neal News: A real-world approach to AI and MLOps

We’ve reached the end of the year and there’s still exciting momentum behind AI in manufacturing, MLOps, and Azure solutions.

Here are a few stories from the Neal team that we think you’ll enjoy…

Migrate on-premises SQL Server to Azure: Which option is right for you?

SQL Server migration decision tree


With Microsoft ending support for SQL Server 2012 in July 2022, it’s worth looking at your next destination. Sr. Technical Architect Rajesh Rai compares Azure VM, Azure SQL Managed Instance, and Azure SQL Database in this article.

How to improve process manufacturing productivity with real-world AI solutions

Learn how real-world AI solutions are improving process manufacturing productivity by…

  • Minimizing start-up time
  • Ensuring end products stay in spec
  • And controlling overall quality

Self-service demo: Optimizing plastic extrusion with AI

Want to see how Project Bonsai can be used to optimize plastic extrusion? Check out this self-service demo Neal Analytics made with Microsoft.




Tutorial: Databricks Spark jobs optimization technique – Pandas UDF

man sitting at computer desk in home office

Xumin is back with another tutorial! Learn how Pandas UDF can be used for Databricks Spark jobs optimization.

ML Operationalization: Building a path to real-world business success

MLOps is positioned to solve many of the same issues that DevOps solves for software engineering

A mismatch in skills, unclear business objectives, and security issues can all create challenges for businesses looking to operationalize ML models. Learn how MLOps and Neal’s methodology can help overcome these obstacles.

In other news…

  • Microsoft held the Put Responsible AI into Practice event this week where experts shared new resources, tools, and best practices for AI development. Here’s the recording and whitepaper.
  • What’s next for manufacturing in 2022? Check out these 4 trends.
  • Data can become “stale” and provide less value over time. Learn more about data-perishability (and what you can do about it).