Predictive Maintenance for Construction Machinery

Dynamics AX proves to be a great platform for managing fleet predictive maintenance. Machine breakdowns cost construction companies time, money, and opportunity. These costs can be managed and minimized if they are planned days or weeks in advance—but how do we predict which machines will be in need of service? Using Cortana Intelligence Suite (CIS) components, we collaborated with…


Introducing a new portal for you to play and learn with us

We have been at work quietly with several of our customers and partners to develop intelligence from their dynamics 365 data. We dug deep into these datasets, created machine learning models and teased out the hidden patterns. However, we have been looking for a way to share what we have learnt in a manner that…


Opportunity scoring for Sales Force

In June 2016, Microsoft team has released a model to score opportunities.’ Earlier with the model, Microsoft team released a solution “Opportunity Scoring” that to score opportunities in Dynamics CRM. Now a solution is also available for Sales Force. If you use Sales Force to manage your sales pipeline – you can download the solution….


Machine Learning Workshop in Charlotte, NC

Hello everyone, Just two weeks ago in Charlotte, NC, the Microsoft Dynamics and Cortana Intelligence team held a 2 day workshop for our Industry Partners at the Microsoft campus off of Arrowood Road.  In attendance was an array of partners who provide Dynamics AX and CRM customers with actionable business intelligence, forecasting and integration support.  We had…


Building a data driven supply chain with Cortana Analytics

EXECUTIVE SUMMARY Dynamics partners have a huge opportunity to reinvent supply chain scenarios and deliver a data-driven application that uses machine learning, optimization solvers and other advanced analytics to embed intelligence and surround the traditional rule-based automated business process enabled by Dynamics. They could do this by dynamically predicting supply chain input. Instead of asking…