The rapid influx of IoT data is changing the way enterprises collect, categorize, and analyze their data streams. The oft-cited Gartner statistic of more than 25 billion IoT devices by 2020 (up from 4.9 billion in 2015) is where Big Data meets the IoT road – data from those connected devices will not only need storage space in a data center, but also the analytics know-how to turn massive amounts of data into actionable and intelligible data.
As a result of this data onslaught, companies are investing more resources into analytics, making it one of the hottest sectors in the technology industry. Predictive analytics – for machine and business data – have direct impacts on revenue and ROI, and investing in that area is a clear win for an enterprise.
ThingWorx Machine Learning, part of the ThingWorx IoT platform, automates the creation and operationalization of advanced, predictive, and prescriptive analytics. A new white paper from ABI Research notes that ThingWorx Machine Learning unlocks the potential of IoT data without the need for in-depth data science expertise, so more data doesn’t mean more time spent on analysis and less time on building an IoT solution. This is a boon for developers who are at the core of rapid app development initiatives whose skill set is not rooted in data science.
Among other findings, this ABI Research white paper outlines:
Learn how ThingWorx Machine Learning is a powerful solution for the analytics challenges faced by enterprises by downloading the Automating and Democratizing Cutting Edge Analytics white paper by ABI Research.
Linda Seid Frembes is a writer and community manager for ThingWorx who blogs about IoT, AR, and technology industry news and trends.