If your enterprise hasn’t yet incorporated the Internet of Things (IoT) into its network, it’s only a matter of time.
Research firm Gartner predicted last November that 6.4 billion connected “things” would be in use globally in 2016, up 30 percent from 2015, with an average of 5.5 million new things being connected every day this year. Gartner expects there to be 20.8 billion connected things by 2020.
As I wrote last June, the explosion of data generated by the IoT creates both challenges and opportunities for enterprises. The challenges include providing enough affordable storage space for IoT data, while the biggest opportunity involves leveraging real-time data through analytics to improve the business.
Indeed, a new joint study by research and consulting firms Camrosh and Ideya Ltd. calls data analytics “the key to value creation in IoT.”
“Having the ability to transform raw device data into useful insights will also offer numerous opportunities and competitive advantage for growing companies that are looking to adapt to the changing digital landscape in a timely and efficient manner,” write the authors of IoT Data Analytics Report 2016. “Companies that integrate their intelligence programs directly into the IoT framework to leverage big data analytics beyond device data will gain the most, while those lacking the capability to convert newly discovered data into actionable insight will be left behind, as data resulting from connected devices will continue to reach peak points of growth in the foreseeable future.”
The study breaks down the IoT analytics products and/or services offered by nearly 50 vendors. It also recommends which products and features enterprises should consider, including data preparation, storage and analysis, presentation, administrative management, security and reliability, development tools and customer service.
Other key considerations should be whether the vendor’s offering can scale to meet your needs, how much experience the vendor has in your industry, and whether the vendor can provide customer references.
Beyond the detailed vendor analysis, the study recommends a framework for assessing the offerings of IoT data analytics vendors:
To create value from the investments made in IoT systems, companies should have a clear understanding of IoT Data Analytics use cases and how they can support their business needs, goals and expected final outcomes from the IoT projects, from data collection to data analysis and insights.
In other words, looking for a vendor without first defining what you need is a recipe for a bad (and perhaps disastrous) purchasing decision.
Does your enterprise have an IoT analytics strategy?