Last week I shared a solution for Scheduling Dynamics 365 workflows with Azure Functions and Node.js. In this post, I will show how to achieve equivalent functionality using Python. The actual Python code is simpler than my Node.js example, but the Azure Functions configuration is much more complicated. First, here’s the Python script I am using. »
Earlier this week I showed an easy way to integrate a Node.js application with Dynamics 365 using the Web API. Building on that example, I have created a scheduled workflow runner using Node.js and Azure Functions. Here’s how I did it. First, I created a workflow in Dynamics 365 that creates a note on an account record. »
For the last several months I’ve been working on an enterprise Dynamics CRM project where one of our goals is to minimize the amount of custom code we write by using North52’s Business Process Activities. I had not been exposed to North52 before working on this project, but I have been pleasantly surprised with how much it has allowed our mostly functional resources to achieve without needing technical assistance. »
On Monday, April 11, at 12 p.m. EDT, I will be presenting a webcast at MSDynamicsWorld.com that will show how a custom integration with Microsoft Azure Machine Learning can be used to perform sentiment analysis on any data stored in Dynamics CRM. Custom sentiment analysis integrations can enable a number of interesting processes in Dynamics CRM including: »
Earlier this year I wrote a post that showed how to perform sentiment analysis in Dynamics CRM using Microsoft Azure Text Analytics. Azure Text Analytics makes it incredibly easy to use sentiment analysis (with English text only), but the full Azure Machine Learning offering is much more powerful. In today’s post I will show how to create a custom predictive web service in Azure ML and make predictions with it in Dynamics CRM. »