03. ThingWorx Analytics
DELIVERING POWERFUL, OPERATIONALIZED ANALYTICS TO SOLUTIONS BUILT ON THE
The Internet of Things is driving a massive increase in the data
available for analysis. 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 insight
from IoT data is outpaced only by the growth of the data itself.
In the Internet of Things (IoT), data is growing at an unprecedented rate. Each device or sensor – each
“thing” – can generate up to millions of data points each day. With the number of connected devices expected
to reach 30 billion by 20201
, managing and extracting value from this data is growing increasingly difficult.
To deliver reliable, actionable intelligence in real time, the
approach to analyzing data must easily and effectively
mitigate the challenges posed by the volume, velocity, and
variety of IoT data.
• Volume: By 2020, IoT data will comprise up to 10% of the
• Velocity: With 3 billion new devices connected every year
on average, data is growing at a uniquely fast pace.3
• Variety: IoT data is found in varying formats for various
objects, in both structured and unstructured formats.
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. These tools will become
too difficult and time-consuming to use when working with potentially billions upon billions of data points in varying
formats. And for IoT users, time is critical – analytics must be contained within their solutions in a way that is both
real-time and proactive to keep IoT operations running optimally. Moving betweenapplications wastes too much
valuable time for IoT decision makers who need analytics to better understand their ecosystems and make critical,