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7 Resources To Make Internet of Things and Machine Learning Easy for Partners

Businesses are coming to the realization that they have to put data to work to stay ahead of the game. Whether that means improving product performance, expanding services with preventive maintenance or predicting what products consumers are likely to purchase, the Internet of Things (IoT) and machine learning (ML) turn data into action. Microsoft and others are making a convincing case that partners of all sizes and competencies are in the right place and the right time to build on the market potential.

There are a growing number of resources that bring the concepts of IoT and ML down a notch, into the practical, real-world business situations that most partners help clients manage. The center of the resource universe is Microsoft's Azure Machine Learning site that provides easy-to-use tools that allow non-developers to build powerful predictive analytics models.  Documentation is approachable and the free trial makes it testable without a big investment.

Not Just for the Enterprise Space
Microsoft's IoT and ML customer stories tend to showcase the large-scale application for enterprise firms like ThyssenKrup and Pier 1 Imports, which can be a bit intimidating for partners who serve smaller customers. But IoT and ML solutions can help every size business. There are plenty of scenarios where partners can provide services to midsize businesses, like:

  • Helping an HVAC (heating, ventilating and air conditioning) company use data from equipment sensors to provide proactive maintenance.
  • Showing a manufacturer how to avoid downtime by putting the production-line machinery data that it has been collecting to work.
  • Using predictive analytics to help retailers fine-tune promotions and e-mail marketing. (See Belinda Allen's tutorial below.)

These types of solutions also lend themselves to packaged service offerings aimed at solving a specific industry challenge -- another way to specialize and differentiate your own services.

Resources To Start the Journey
For every partner, the success of adding a service line is, in large part, dependent on the interest and enthusiasm of your team. When employees are excited about the possibilities of technology, you don't have to ask them to follow the learning path -- they'll pursue it on their own. With that in mind, the list below is a place to start the journey in evaluating the opportunity of IoT and ML.

  • ConnectTheDots.io is a new open source project by MS Open Tech that will help you get started connecting tiny devices to the cloud and analyzing data through Azure services.

  • Microsoft's Internet of Things Blog is building a good knowledge base of IoT-related topics. Hopefully, more partner stories will make their way to the blog as IoT solutions go mainstream.

  • Microsoft Internet of Things YouTube channel is another source for inspiration.

  • Microsoft MVP Belinda Allen's tutorial on Predictive Analytics is an excellent video, providing advice for undertaking predictive analytics projects, plus a technical demo of Azure Machine Learning.

This list of introductory resources is not meant to suggest that building an IoT and ML practice is easy. Achieving Microsoft's Intelligent Systems competency, which demonstrates your proficiency, requires a commitment to training, proving execution capability with customer references and significant fees. But it's all achievable if you decide that IoT has the potential to add value to your customers and build your business.

The bottom line is that IoT and ML aren't just a play for the big consulting firms. Find the person in your company who is interested in solving challenges and point them to these resources. Build the excitement and interest in the organization and establish your game plan. There's no reason that you shouldn't be able to ride the IoT and ML wave.

How are you taking advantage of the IoT and ML service opportunity? Add a comment below or send me an e-mail and let's share your story.

Posted by Barb Levisay on February 25, 2015


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