IoT Data offers an unparalleled level of insight that can be acted on in real time to drive real outcomes. ThingWorx customers can now lower the entry barrier to analytics and are turning their connected product data into meaningful insights that translate to business value!
Smart, connected things, by definition, generate data – and within that data lays a wealth of previously unattainable, invaluable insights. As the number of connected devices grows into the billions, the demand for more, better information from IoT data is outpaced only by the growth of the data itself.
Traditional reporting and visualization approaches are not well-suited for IoT data analysis. They can be complex, typically require some manual intervention, and yield limited visibility and insights. For IoT users, time is critical – analytics must be contained within their solutions in a way that is both real-time and proactive.
To find the true value in IoT data, organizations must be able to deliver powerful, automated analytics capabilities to solutions – including real-time pattern & anomaly detection, automated predictive analytics, and contextualized recommendations.
By 2020, it is estimated that industrial IoT companies will nearly double their investments in IoT analytics. Effective techniques for extracting and managing data are no small feat, but companies that can harness their IoT data are poised to gain enormous dividends. Learn methods and technologies used by today’s IoT innovators to gain the edge in security, customer satisfaction, and optimal operational efficiency. Read this O’Reilly white paper as the first step in mastering industrial IoT analytics, and claiming decisive competitive advantages.
Watch this webcast to understand how you can tackle the challenges associated with the volume, velocity, and variety of IoT data and how you can use ThingWorx Analytics to quickly and easily add real-time pattern and anomaly detection to your capabilities, and more.
Automate the creation and operationalization of advanced, predictive, and prescriptive analytics. For application and solution developers, it provides an easy way to use advanced analytics methods without requiring expert training in data science, complex mathematics or machine learning.