Most organizations face a growing number of data storage challenges.
The number of applications and services IT departments support are increasing; with users accessing data from everywhere, at any time, and from different devices.
The variety of workloads are increasing as well, with applications competing for resources from the same infrastructure.
The cost of traditional infrastructure is incompatible with the exponential growth of unstructured data, big data workloads, or Internet of Things (IoT) applications.

The traditional classifications of primary and secondary data, that correlate primary with structured data/databases and secondary with unstructured files, are no longer valid.
With data becoming one of the most important assets for organizations, structured and unstructured data are now equally important, and they should be protected and treated accordingly.

A new primary/secondary classification has emerged and is based on the value of data, with data indexation and classification.
Coupling this new classification with a two-tier storage infrastructure can help reduce costs and simplify the process, especially if the two tiers are integrated and data can move seamlessly between them.
Modern applications can now be divided into two families: latency-sensitive or capacity-driven.
The first group needs data as close as possible to the processing engines (e.g. CPU, GPU, etc.) while the latter usually requires easily accessible data spanning multiple devices across the network.

New infrastructure designs must take this division into account to cope quickly with new and ever-evolving business requirements.
In this report, we analyze several aspects of the two-tier storage strategy including:
Key findings include:
Source: gigaom.com
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