Scalable Analytics

Use Cases

Scalable Analytics is earning the reputation as the data-in-motion problem solver for business, industry and government.

Smart Grid and Streaming Sensor Data The data center is a growing source of streaming sensor data that should be used to improve the center's operational efficiency. The number, density, burstiness and location of sensor streams are almost endless within a "green" facility or campus. Scalable Analytics is capturing real-time sensor readings from data center racks of servers, components, devices and building infrastructure. Our tools are helping owners, operators and managers of these facilities and the new breed of cloud providers to help them compute more while consuming less.

Wall Street Scalability is the New Capability. Are you experiencing hitting the "brick wall" when running R--the open source statistical package? You are not alone unfortunately. Scalable Analytics has removed the performance barriers of R and other similar statistical libraries or packages. Our R-flow product focuses on scaling the computational and data flow of these tools. R-flow makes it possible to perform statistical and other mathematical routines, in parallel, over a wide-range of model parameters quickly and securely. Scalability is rooted in our name for a reason.

Hadoop Beyond Hadoop Extreme data, the ability to handle unstructured or textual data, and a scalable architecture signals the end of the Hadoop movement. Scalable Analytics has worked with extreme data providers like an E-bay data distributer and a micro-donation platform provider to quickly investigate text-based relationship analysis. Hadoop was a solution choice for descriptive analytics yet our clients have moved beyond the usefulness of Hadoop to real-time, predictive analytics: solving their data-in-motion problems.
eBay Real-time Analytics High volume data, high velocity data streams, real-time viewing and analytics continually stokes the fires at Scalable Analytics. We begin with the financial services industry who demanded real-time analysis tools built on open standards and high-performance infrastructure. Scalable Analytics delivers an appliance with real-time data-mining and analysis modules. A theme of ours solving the high volumes, high velocity, high varieties data streams problems. Couple our innovative relationship-based visualization client to the analytics and you have analysts viewing the important relationships in real-time.

Meaningful Differentiation
Meaningful Differentiation

Integrated Secure Messaging Framework: Scalable Analytics provides a secure and scalable software framework that integrates user-level process model into a fast messaging layer. The importance of user-level processes allows for user-level scheduling strategies that make it possible to make efficient use of multicore while integrating this into fast inter-node communication libraries.

Agile Systems-of-Systems Approach: Scalable Analytics has developed a fully dynamic system with flexible configuration for negotiating channels and the run-time environment. The Appliance flexibly maps computation onto to compute resources and dynamically balances loads for optimal throughput and performance.

Service-Oriented Parallel Structure (SOPS): Scalable Analytics is engineered on the concept of large-scale service-oriented parallel structures that provide a set of service-oriented interfaces to the parallel processing modules of the system. For example, a SOPS can be a scalable robust correlation service that takes in arbitrarily large number of streams and dynamically provides, on a subscription basis, correlation among streams.

Scalable Analytics leverages its strategic process and capability to create differentiation — its unique story: Delivering faster insights on extreme data.®

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