Vehicles are more than transportation: they’re now smart mobile devices generating volumes of telematics data. Automotive revenue streams are shifting and extreme analytics are the key to unlocking the value from this big data.

  • Connected cars generate 300TB of data per car, per year
  • By 2020, connected car services will account for over US $40bn in annual revenue
  • By 2030, half the world’s vehicles will be covered by telematics-based insurance policies

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The OmniSci Extreme Analytics Platform:
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Vehicle Telematics for Carmakers

The Challenge

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.

OmniSci Solution

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.

McKinsey & Company

Monetizing vehicle data for business opportunities and customer benefit

McKinsey & Company

Capitalizing on vehicle data by offering usage-based insurance contracts

Deloitte

Challenges and opportunties of usage-based insurance programs

Predict Machine Failure with IoT Data

The Challenge

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 Solution

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.

GTC Presentation

Volkswagen Uses OmniSci to Visualize and Interrogate Black Box AI Models

Forbes

Blending Man And Machine To Get The Most From AI

IoT Agenda

Five ways IoT is transforming the manufacturing industry

Location and Mobile Services

The Challenge

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.

OmniSci Solution

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.

OmniSci Customer Case Study

How Skyhook uses OmniSci for location intelligence and insights

RTInsights

Using Extreme Analytcs to Deliver Compettve Insights in Telecommunicatons

OmniSci Video

OmniSci overcomes the data challenges of speed, scale, and real-time interaction, to provide telecommunication carriers instant insights from datasets too big or too fast for traditional analytics platforms.

Rapid Response to Cyber Incidents

The Challenge

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 Solution

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.

Watch OmniSci Demo

See how OmniSci Immerse interactively explores your Google Analytics data

Ponemon Institute

How malware destroys an organization’s reputation and financial stability

eSecurity Planet

Industry experts discuss how AI is shaping the future of IT security