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Benefits of Simplifying Enterprise Storage Architectures


Guest blog written by Bill Mannel, VP & GM – HPC, Big Data & IoT Solutions, HPE Servers

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We’ve all heard the stats, and they can be hard to comprehend.

Over ninety percent of all the data in the world has been generated over the last two years. By 2020 more than a trillion applications will exchange 58 zettabytes of data across over 100 billion devices. Annual spending on Big Data technology and services will grow to represent $48.6 billion by 2019.

There’s no question that Big Data is mounting at staggering rates, and if you haven’t already, now is the time to implement new ways to extract value from data and leverage it toward achieving better business outcomes.

Data proliferation has put pressure on companies across every industry to reevaluate how they collect, organize, and store their data assets, and driven the adoption of storage technologies which manage data more intelligently while lowering costs and IT complexity.

Manufacturers must archive large volumes of data collected from various sources in order to generate operational insights, track production output and maintain compliance. Optimized data storage practices are a must for organizations that regularly manage vast libraries of structured and unstructured data, and require long-term retention and immediate retrieval capabilities.

Companies face overwhelming challenges like reducing the complexity of their traditional storage architectures, increasing storage capability to meet the demands of their growing data volumes, and accounting for the rising costs of their necessary storage investments.

According to a 2015 report from the Evans Data Corporation, storage costs ranked as one of the top three barriers that keep organizations from gathering and using Big Data to the best of their abilities.

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Many organizations are transforming the way they manage their storage infrastructures, choosing to employ a primary storage level along with an active archive to safeguard their most valuable data assets. This method allows organizations to dedicate primary storage to hot data which needs to be served up and accessed on a frequent basis, and use an active archive to provide immediate and continuing access to legacy data while driving down costs by storing it on a less-expensive media type.

This type of two-tiered storage architecture can offer a number of operational improvements to IT departments, including:

  • Massive flexibility for scaling up to support growing data volumes in real-time.
  • Decreased IT complexity and the convenience of having fewer storage tiers to deploy and manage.
  • Greater efficiencies to data management and user experience, with the added benefit of being able to perform updates and maintenance activities quickly and with very little downtime.
  • Improvements to data security at a lower cost per TB and significant reductions to overall storage costs.

Simplifying storage levels enables users to readily move data back and forth between tiers as necessary. Data that is no longer needed on a frequent basis can be seamlessly moved from primary storage to the active archive, and moved back again in an instant to fulfill compliance demands or respond to a regulatory event.

Object storage solutions can help organizations cut costs, accelerate time-to-value, and support current and future Big Data initiatives. Software-based storage and purpose-built hardware optimized for storage-intensive workloads are designed to support today’s petabyte-scale storage needs, and offer organizations breakthrough levels of performance.

With Big Data expanding at ever-increasing rates, a transition to simpler storage architectures will allow companies to maximize storage capabilities, and at the same time, lower technology costs and complexity, giving them the chance to focus on data optimization for driving smoother operations and stronger business growth.

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About the Author


I am a Senior Manager managing external content and social media for HPE Servers Awareness. Stay tuned for topics on Mission Critical Solutions, Core Enterprise and SMB Solutions, Next Gen Workload Solutions, Big Data and HPC, Cloudline and HPS Options! Follow me @RubyD_Nich