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Storage Best Practices for Each Stage of the Data Lifecycle

RubyNicholson

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

Big Data offers unprecedented opportunities for organizations to improve the customer experience, drive operational efficiencies, and inform business decisions. However, explosive data growth can be a mixed blessing for those that haven’t yet implemented standards and adopted new strategies for supporting rapidly expanding data volumes.

This environment has put immense pressure on IT departments to uncover ways to better collect, manage, and store data in order to realize its full potential. As data expands into the zettabyte realm, organizations must adapt their approach to storage in order to improve the management and performance of data over each stage of the lifecycle.

Effective data lifecycle management (DLM) ensures information is intuitively organized for easy discovery, highly available for serving up business insights, and stored properly and cost-effectively given its stage in the lifecycle. Organizations that adopt best practices to DLM will be able to reduce storage costs, increase performance, and enhance the ability of data to support business goals.

The data lifecycle, or the movement of data from collection to preservation, has elongated over time as today’s data-driven organizations continually process, repurpose, reuse, and analyze data multiple times throughout its lifecycle.

The sheer volume, variety, and velocity of data have made daily management a major challenge for organizations wishing to extract maximum value from their data. However, a few proven best practices can help companies significantly improve the performance of their storage infrastructures at each stage of the data lifecycle.

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Classify Data Types to Define Storage Needs

Evaluating data types according to storage needs can begin in the data collection stage but is an ongoing process lasting throughout the lifecycle. Start by classifying data according to a few key factors, including:

  • Importance to everyday business operations
  • Required degree of availability/accessibility
  • Retention timeframe, taking into account business needs as well as regulatory/compliance requirements
  • Storage needs once data is retired and ready for archiving

Using these insights, a storage hierarchy can be created to designate a level of access, data security and retention policies, and appropriate storage media for each stage of the lifecycle.   

Simplify Tiered Storage Models

Some organizations are choosing to adopt simplified storage architectures which employ only a primary storage level along with an active archive to safeguard their most valuable data assets. Scaling back to two tiers allows organizations to dedicate primary storage to “hot data” which needs to be accessed frequently while using an active archive to provide immediate and continuing access to legacy data, thereby decreasing IT complexity and offering the convenience of having less storage tiers to deploy and manage.

Implement an Active Archive

Active archives are an ideal storage method for companies that regularly manage large volumes of data and require access to all of their data all the time. An active archive provides users immediate and continuing access to archived data while storing it on a less expensive media type, leaving primary storage free for data which is needed on a more regular basis. Organizations can take advantage of limitless storage capabilities to house their most valuable data resources, reduce storage expenditures and TCO, and increase the availability of archived data to users across the organization.

Leverage Technology for Automation

Investing in high-performance computing technologies to help automate storage and data management processes has become crucial to survival in this new style of IT. Applying automated rules-based classifications, as well as retention and data disposal policies are just a few options for automating storage processes to free IT from constant in-house management.

Expanding data volumes have driven a need for organizations to adopt new ways to manage the multitude of information at their disposal. Implementing best practices to improve storage infrastructures and address storage needs at every stage of the data lifecycle can help organizations control the costs of IT, exploit smarter data management capabilities, and realize performance improvements across the enterprise.

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About the Author

RubyNicholson

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