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03. ThingWorx Analytics


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 world’s data.2
• 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, informed decisions.

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