Data Intelligence made simple

All About Data Intelligence

Administrators and IT leaders are always on the look-out for ways of improving the performance of their storage infrastructure. Improving storage speed without investing in additional infrastructure has been something of a Holy Grail for administrators.

This calls for a paradigm shift– from thinking about storage, to thinking about data.


Data housed in a storage device or other electronic medium, that is accessed frequently or continuously as part of a business process. Understanding the dynamics of this active data and managing data movement dynamically, based on workloads and application requirements, is really the key to improving data performance.


Implicit in understanding the dynamics of active data and managing it, is the capability to see, monitor, and track active data over a period of time and to understand what is happening in relation to different applications. Different applications have different I/O footprints. Real time tracking and monitoring critical I/O parameters and data delivery operations is vital to understanding what is happening to the data in system.


Through I/O level control, adapting the data delivery system to different workloads and to different application requirements is an imperative for improving performance. This would include deterministically modifying data paths, data pipelines, as well as data communication channels in grids.


Boosting read/write speeds across physical, virtual, rack, data center, and grid environments – ultimately, that is the proof of the pudding. Typically, increasing IOPS and reducing I/O latency are two processes which contribute to improving speeds. Traditionally, storage systems keep data away from CPU and applications. Moving active data closer to the CPU and to applications is the key to improving performance.

Data Intelligence / Data Analytics

Data Intelligence is a management insight platform, based on real time information, gathered and analyzed from a file level, as well as a strategy level. It gives IT leaders visibility, control, and acceleration of active data in their system.

An analytical engine performs I/O analysis and delivers robust insight into application I/O behavior. Deep file level analytics coupled with a management console enables admins to identify and accurately size SSD requirements. It empowers admins to take better decisions and to drive these throughout the environment, for improved storage performance, work productivity and costs.

Scaling Big Data

Flexibility for growth is critical to any large data center and demands for performance & capacity continue to grow exponentially. By monitoring application specific IOPS and ensuring applications have the data they need close to the CPU, admins are able to dramatically increase available IOPS and reduce I/O latency.

Data Policy

Cache technology has become standard for acceleration of data within the server. However IT Administrators are left to their own devices in understanding how to utilize caching to its full potential.

In majority storage systems, default policies often commit the data to the write source after the initial read, slowing down even the simplest of workloads. By writing huge volumes of data directly to storage without first thoroughly understanding it IOPS utilization rises, often resulting in expensive hardware purchases for additional IOPS capacity.

Real-time reporting and analytics of active data give administrators the power to understand and fine tune cache rules for their entire environment and to create policies to optimize I/O.

Data Policy

Intelligent Grid Management

Intelligent Grid Management

Grid computing is complex by nature and distributed computing environments present a unique set of challenges for data management. Traditional grid networks keep data away from the server, relying on expensive NAS and SAN storage to retrieve and deliver the data that applications require, while CPUs remain idle.

With data analytics, administrators can ensure data is delivered to the correct machines at the correct time for optimized I/O performance. Keeping data closer to the compute nodes, making data smarter and faster all at once.

Intelligent NAS Deployment

In both large and small environments, network storage appliances are often overloaded during peak demand periods. By intelligently caching critical data on the server itself, traffic reduces across the entire network, resulting in a smoother, faster, and more efficient application environment.

Intelligent NAS Deployment