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The Extreme Data Economy
Beyond Big Data, Data is the Business

The Extreme Data Challenge

From healthcare to energy, telecommunications to retail, logistics to financial services and more, the expansion of mobile, social, and cloud technologies led to the big data phenomenon: using data to make better business decisions across industries. Data streams have grown in volume, velocity, and variety. But storing and managing this data isn’t enough anymore.

As IoT devices and new data sources proliferate, data has never been as unpredictable and analysis as complex. Data may be big or small, static or streaming, structured or unstructured, long-lived or perishable, human or machine. Siloed legacy databases built for serial computing just can’t keep up.

COMPLEXITY OF ANALYSIS UNPREDICTABILITY OF DATA TRADITIONAL DATA Data-Validated Business In the Manufacturing Economy, data validated previous decisions. BIG DATA Data-Informed Business In the Service Economy, data was analyzed to make decisions. EXTREME DATA Data-Powered Business STREAMING DATA In the Extreme Data Economy, data decisions are autonomous.

We've moved beyond big data. We’re now experiencing an elemental shift from the service economy, informed by data, into the Extreme Data Economy, which runs on it.

A business’ most valuable asset isn’t a product or service. It’s data. But in the Extreme Data Economy, that data is only as good as the sophistication and speed of analysis.

Businesses must take action now: deal with the data deluge or drown in it.

Serial Computing

CPUs are unable to process data efficiently

Legacy databases can’t handle extreme data because they’re built for serial computing, not the IoT. But data analysis isn’t a linear task anymore. Saddled with legacy databases, companies can’t process the volume, velocity, or variety of data they receive in real-time, limiting their ability to analyze and act on that data.

Serial Sprawl

Big data systems are sprawling out of control

With every new use case comes a new point solution. This cul-de-sac approach to technology has led to data silo after data silo, with no centralized way to process, manage, or connect data quickly or easily.

The Insight Engine for the Post-Big Data Era

When extreme data requires companies to act with unprecedented agility, Kinetica powers business in motion.

Kinetica was built from the ground up as an all-in-one, GPU-powered instant insight engine for advanced parallel computing. We won’t be held back by serial computing or serial sprawl. Our hardware scales to process massive data sets in parallel, designed to manage unpredictable complexity, volume, and speed.

Get instant answers to complex data questions as the data streams in. Personalize services in real-time, make informed business decisions on the fly, and turn data itself into valuable new revenue channels.

Kinetica harnesses the compute power of GPUs to solve complex data problems
64 CPU cores
Serial Compute
5000+ GPU cores
Unparalleled Compute

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Are You Ready for the Extreme Data Economy?

Forward-thinking companies are creating new opportunities with Kinetica

RS Energy Group use real-time pipeline, well, and spatial data to pinpoint viable oil fields and remotely monitor drilling performance

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GSK’s data science and analytics teams use Kinetica on existing GPU infrastructure for advanced and innovative use cases.

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Lippo Group, with businesses across telco, finance, retail, and healthcare, gained a 360-degree view of their customers across industries with real-time personalization

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New White Paper

BI Meets AI

Augmenting Analytics with Artificial Intelligence to Beat the Extreme Data Economy.
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GPU Data Analytics eBook