Most companies today are simply “drowning in data” because so much data (much of which is unstructured) is generated in the modern enterprise that it is near impossible to unlock the insights buried within this rich information.
IoT, and the volume of data now being produced by sensors (most of which doesn’t relate to other sensors or data sources and is extremely noisy or missing data) and analytic challenges take on an entirely new scale. • Combine the massive, noisy data volumes with fundamental shortages of human capacity (lack of data scientists and skilled analysts in nearly every industry), and organizations simply can’t analyze data effectively.
and powers data science by combining purpose-built analytic components and powerful visualizations across varied sources - including Internet of Things (IoT) sensors, Big Data, and Video - with unprecedented machine-learning capabilities.
utilize powerful machine-learning capabilities to surface actionable insights, including hard-to-find anomalies and correlations within and across disparate data sets and sources, to drive informed decisions and next best actions, in real time. • Our solutions are Enterprise-ready. Built on a scalable platform - delivered in the cloud or on-premise – we enable a broad range of use cases for a wide variety of users including data scientists, business analysts, application developers and operational managers.
IoT have been proven in use at some of the most demanding and sophisticated IoT environments worldwide. • Our IoT analytic components are also edge-enabled, making them deployable in highly distributed manners, such as embedded into sensors, video cameras, network devices and industrial equipment, reducing the overhead and bandwidth requirements of collecting data from the tens, hundreds or thousands of different sources widely deployed in common IoT environments.
value add? • Our Data Fusion capabilities allow data from nearly any source (such as sensors, cameras, customers, databases, infrastructure, devices - even sentiment) - to be ingested, normalized and rationalized. • Then, data is applied against purpose-built, analytic models and sophisticated machine-learning algorithms designed by our team of world-class data scientists for a wide variety of use cases to identify anomalies, behaviors and correlations, enabling businesses to discover unprecedented insights, and act upon them, quickly.
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