Savi launched Savi Insight, the first-ever cloud-based sensor analytics solution for the Internet of Things (IoT). Savi Insight gives executives, line managers and business analysts access to analytics that transform sensor and other machine-generated data into real-time operational intelligence. Savi Insight’s combination of predictive modeling and visualizations accelerate decision-making, identify and help mitigate unforeseen risks, and improve operational performance and profitability.
Savi Insight collects and correlates vast amounts of sensor and machine-generated data and mashes it with information from enterprise systems and independent data sources such as weather, traffic and social media. With easy-to-understand visualizations, Savi Insight makes every individual in an organization a ‘knowledge-worker’ without the requirement of being a data scientist or business analyst.
Sensors Key Driver in $16B 2014 Market
A recent compilation of industry research found that sensors are the largest and fastest growing segment of connected devices, more than twice number of smartphones worldwide. By 2020, sensors will account for approximately half the predicted 50 billion connected devices in the Internet of Things.
"The rapid proliferation of connected, sensor-enabled devices (Internet of Things) is one of the significant drivers for Big Data technology and services, a market that will top $16 billion in 2014, growing at a compound annual growth rate of 27 percent over the next five years. Savi Insight delivers value via predictive analytics leveraging sensor data to help optimize real-time decisions on materials in motion," said Henry Morris, senior VP of worldwide software and services at IDC.
“Many are talking about the Internet of Things, but don’t realize how tricky it is working with wireless devices in real-world settings. You have to deal with dead zones, intermittent connectivity, long latency and other vagaries, especially in remote places. Further, it takes time to learn what the different data patterns really mean,” said Bill McBeath, chief research officer, ChainLink Research. “Savi has decades of experience and hundreds of deployments for logistical applications across the most extreme of environments and has continually refined their platform and solutions. They are one of the most prepared and well-positioned companies to take advantage of the growth of sensor-oriented IoT applications.”
Architecture Combines Deep Analysis with Real-Time Transaction Processing
Savi Insight is powered by the innovative Savi Hybrid-Lambda Architecture, which provides all the analytic benefits of the “Big Data” Lambda Architecture without sacrificing the mission-critical consistency of real-time online transaction processing. By combining a relational database, complex event processing and schema-less data technologies, Savi’s Hybrid-Lambda Architecture can perform streaming analysis of data in motion, manage real-time transactional response by end users, explore historical patterns, learn from itself and predict future outcomes – at scale, all from one architecture.
3-6 Week Deployment with Savi Scenarios
Savi Insight utilizes unique, pre-packaged, state-of-the-art analytics called scenarios that address specific business conditions or challenges by combining business logic, data science and expertise. Scenarios identify specific events, activity sequences or related attributes among disparate data. Unlike time-consuming and costly platform approaches that use generic big data tools and lack sensor domain expertise, Savi Insight scenarios get organizations up and running in as little as three to six weeks, generating results in a fraction of the time and cost typical of other vendors’ big data initiatives. Savi Insight includes several scenario categories including Assets in Motion, Static Assets, Commodities and Consigned Assets, Risk Management and Compliance, Risk Maps, and Operations Excellence.
Visualizations in Savi Insight simplify decision-making for all types of users through paired tables, interactive sorting, filtering and highlighting capabilities. Organizations can use a wide variety of visualizations including tree maps, histograms, geomaps, comparative bars, time series and heat maps to quickly extract insight and share findings internally.