A single connected car can generate over 300TB of data per year. Multiply that by millions of vehicles, and the aggregate volume of streaming telemetry data will easily overwhelm mainstream analytics platforms. An increasing number of signals and sensors from telematic devices for motor vehicles can now relay critical insight into vehicle performance and diagnostics, navigation and infotainment preferences to automotive engineering and design teams. Yet this wealth of vehicle telematics data is valuable only valuable to those with the ability to process it, analyze it, and visualize it in its entirety.
The OmniSci Core SQL engine delivers query results with supercomputer speed. Those results are then immediately available for visual exploration via the OmniSci rendering engine and visualization front-end. The integrated analytics platform helps vehicle manufacturers visualize and interact with billions of rows of vehicle telematics data, rapidly discover new insights to improve vehicle performance, driver safety and fuel economy. Derive spatiotemporal insights for innovation on an entire line of cars or trucks, or drill down to a single vehicle sensor at single point in time, all in milliseconds.
Artificial intelligence is increasingly used to predict machine failure, to minimize downtime and maintenance costs for automobiles, ships or aircraft. Yet engineers have trouble explaining an AI model’s black-box recommendations, so leaders fall back on human experience and "gut" guesses in favor of automated recommendations to keep field equipment running as intended.
OmniSci's extreme visual analytics make AI models more accessible to the scientists who create them and to the broader audiences of business leaders, military commanders or regulators who must understand those models. With immediate visual exploration of the same underlying elements that trained AI models, anyone can trust their predictions.
Location-based metadata can create a wealth of new business opportunity. Yet this stream of data scales too quickly for developers who want to create apps showing relationships between the location of people and equipment to other operational data. Existing analytic engines cannot keep up with the scale and speed of today’s operational data.
The OmniSci Core SQL engine was designed for this new era of location intelligence. It can process billions of rows of structured data in milliseconds and visually render those with the same speed. This dramatically accelerates operational analytics, marrying vital business datasets to mobile location metadata. Because OmniSci Core is open-source, in-house or third-party developers can easily create new apps to deliver analytic apps for exploring layers of operational location data.
How Skyhook uses OmniSci for location intelligence and insights
Unauthorized intruders infiltrate systems of national governments and global corporations by hiding their tracks across identities, devices and behavior. Teams in Security Operations Centers (SOCs) receive countless incident alerts, but most are false alarms, so SOCs waste thousands of hours a year investigating those. When an actual attack has occurred, slow analytics across fragmented data make it harder for security teams to identify and patch vulnerabilities before more data is compromised.
OmniSci's zero-latency visual analytics don't require pre-aggregation. In this cat-and-mouse game, that speed gives security analysts immediate insight. They can perform hundreds of queries in quick succession, without losing access to any granular information. SOC teams can investigate far more cyber alerts every day, and when they do find a vulnerability they have the data they need to apply the right patch quickly, maintaining an ongoing patch cadence that deters future attacks.