Getting Started in IoT Analytics
EVERY IT INTEGRATOR can handle the first step of an Internet of Things project: Install, manage, connect, and secure IoT devices. The next step, maybe not so much: Mine all that data for actionable insight.
“The data is the important part,” says Aditya Pendyala, co-founder and vice president of growth at Mnubo, a developer of IoT analytics and artificial intelligence solutions in Montreal.
“Analytics enable the data strategies and business insights needed to drive successful project and business outcomes,” says Azmat Tanauli, senior director of product strategy for Birst, an Infor company and global provider of cloud business intelligence headquartered in San Francisco.
Indeed, profits will ultimately come from the data, not installing the IoT devices. But analyzing and managing all that “dirty, heterogeneous data” is difficult, according to Pendyala.
Tanauli explains that system integrators need an understanding of modern data architectures and the ability to refine and cleanse complex data sources. In addition, they must know how to handle the data securely, feed it into a modern analytics platform, and support multiple outputs—for dashboards, mobile devices, and even embedded analytics in application workflows.
DIY or Boxed Solution?
There are two ways for channel pros to develop tools for proper IoT analytics, says Pendyala. “They need to decide if they have a Home Depot culture to build it themselves, or an Ikea culture looking for in-a-box solutions.” There’s no wrong answer. DIY companies look to platforms like Microsoft Azure or Amazon Web Services, he says. Those seeking a “packaged” vertical solution can turn to companies like Manna, for example, which offers a platform for monitoring and analyzing oil and gas equipment.
Partnering with data and analytics companies has become a popular option as well, especially if you’re seeking vertical know-how, according to Tanauli. “IoT analytics partners can bring in the subject matter and industry expertise needed to drive project success,” he explains. Mixing the right amounts of in-house knowledge and partner capabilities will create a winning combination.
Before choosing partners, though, Pendyala recommends doing some advance legwork. “First step is to create a working or cross-departmental group, and ensure the foundational elements are there,” he says. These include security, IoT data, and other business data to mix and compare with the IoT project data.
While many IT providers start by hiring a data scientist, that may be the wrong approach, Pendyala says. Look instead, he suggests, for domain experts who can derive insights from the data and draw conclusions for ways to apply that information to improve business processes.
IoT cases in different industries require different analytics capabilities, adds Tanuali. Be clear on what business outcomes are desired from an IoT project, then identify and collect all the data needed to arrive at actionable insights.
Warning: This step can be hard. Data will be in different formats, missing, and in need of cleansing or other care before you can trust the results. And after you finish that long list, you will still need a way to transform the data into visual insights delivered in the most appropriate way for your users; in other words, graphs, charts, and alerts.
Pendyala learned a nice lesson about IoT data analysis early on. “Some of our highest ROI cases have been those with the least complex analytics,” he says, such as changing to use-based equipment upgrades from calendar schedules for maintenance, or tracking shipment locations and temperature controls with IoT sensors.
Pendyala cautions that while getting involved with business processes and strategic technology might be unfamiliar territory for IT providers and integrators, embracing IoT analytics will move you up to a new level of professional support for your clients.
JAMES E. GASKIN is a ChannelPro contributing editor and former reseller based in Dallas.
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