Working with Microsoft Azure is like walking on a moving sidewalk in an airport: you are walking at the same speed as other travellers, but you reach your gate twice as fast. Last week, at Microsoft’s annual developer conference, Build, the company announced a host of Azure analytic capabilities that will underpin the exploding Internet of Things (IoT) marketplace. The new Azure analytics and data storage capabilities open up huge, cost-friendly, value-creating possibilities for companies to harness the data they collect.
First off, let’s talk about IoT, which is much more than just devices and their data. IoT is not about just gathering data; it’s about making sense of that data and acting on it to improve customer experience. The “connected devices” concept is important, but doesn’t capture the vastness of the opportunity.
So the real value in the Internet of Things is in integrating the data that devices collect with the existing pool of operational information a company maintains, then mining that vein-rich aggregation to generate insights that drive business decisions. What Microsoft did was create a variety of prewired services for analytics and data storage—such as Azure Data Lake, Azure SQL Data Warehouse, Azure Machine Learning, Azure HDInsight, Azure Event Hubs and Azure Operational Insights—that open up huge possibilities for IoT by turbo charging the ability to create systems to monitor, aggregate and analyze huge amounts of data.
From my perspective on the moving sidewalk, what those analytics services mean for customers is that technology that used to be complicated (and costly) to implement has become more modular, more component-based. When considering an IoT application in the past, customers had to factor in custom “plumbing.” The new Microsoft analytics options mean that we don’t have to build extensive, expensive internal structures for each customer because now much of it already exists. So my customers can move faster than their competitors who still have their feet firmly on the floor building IoT plumbing.
Think about this scenario for our customer that manufactures commercial-grade ice machines (the kind you would find in a hotel or bar). Currently the company gathers data on each machine’s health manually via maintenance people on service calls. With IoT, installed sensors can constantly gather data about each ice machine’s temperature, water pressure, compressor cycles, time between each tray flip, pattern of usage, etc. But since the data is useless without analytics, we can use the new Azure analytics services and Azure Machine Learning to build a predictive model that will help us pinpoint when an ice machine is likely to be in need of maintenance and send a service technician to calibrate the machine before it breaks down.
The obvious impact of those new analytics is that the ice machines remain in service more efficiently. But let’s think about the other trickle down (sorry, ice pun) effects:
- The bar owner using the ice machine never needs to worry that his Saturday night revenue will be impacted by an outage. As a result he’s willing to pay somewhat more for that guarantee.
- The ice machine company can charge more for both maintenance (since the bar owners are willing to subscribe to a more dependable service) and for the machine itself since it is now differentiated from competitors by its level of reliability.
- The ice machine company’s cost of providing maintenance will be reduced because they can now predict potential outages and service those outages in advance during regular business hours.
- Bar vendors such as liquor companies want to understand ice usage patterns so they can better supply their customers and adjust their marketing and sales. They could purchase ice usage pattern analytics from the ice machine company, who would be adding a revenue stream that didn’t exist until now.
The new analytics services from Microsoft didn’t change any of the possibilities of IoT, but they opened the door to cost-effective, low-risk implementations for untold numbers of interactive scenarios. Once again, because of the new Azure analytics services—just as when PaaS came on the scene—the cost to explore and innovate is less than the opportunity cost of standing still. Of course this is all relatively new, and right now it’s not 100% clear where all the value is, but companies need to start finding out. Bottom line, Microsoft turned on the innovation engine—again—so all you walkers better get on the moving sidewalk or miss your flight.
Photo by Steve Hopson Photography