Alexandria, Va.—May 2, 2014—Signaling a new era in big data analytics, Savi launched Savi Insight, the first cloud-based sensor analytics solution for the Internet of Things (IoT). Savi Insight gives executives, line managers and business analysts immediate 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 accelerates decision-making, identifies and helps mitigate unforeseen risks, and improves 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.
“Savi Insight gives organizations an immediate and clear understanding of their operations that is based on real-world facts,” said Bill Clark, president and CEO of Savi. “Savi Insight recognizes relationships between assets and actions by combining the very complicated and unstructured world of sensor data with enterprise systems and third-party data. It examines and explores those associations to create operational intelligence that organizations can use to improve efficiency, reduce risk and solve new problems.”
According to Ralph Harris, president of Decade Products, a manufacturer of a complete line of reusable plastic containers and pallets for industrial, agricultural and food processing applications worldwide, “Savi’s ability to capture data from any sensor was a clear differentiator and allows us to leverage our existing sensor investments. With Savi Insight, we are able to test different what-if scenarios and use predictive analytics capabilities cost-effectively.”
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 may 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 $16B 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 vice president 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 in extreme environments, and continually refines its platform and solutions.”
Architecture Combines Analysis with Real-Time Transaction Processing
Savi Insight is powered by the Savi Hybrid-Lambda Architecture, which provides all the analytic benefits of the big data Lambda Architecture without sacrificing the 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.
“Savi Insight combines big data technologies in a novel approach that helps to uncover and visualize patterns occurring in a multitude of data sources, and it gives organizations new advanced analytical capabilities to play high-level business scenarios with low-level, high-volume sensor data,” said Dr. Tom Dybala, founder and principal at Exprentis, a knowledge engineering and data mining company.
Three- to Six-Week Deployment with Savi Scenarios
Savi Insight utilizes unique, pre-packaged 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 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 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.
Dynamic 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.
