FINAL WORD
Why designing your data storage architecture is important
Using flash , moving to software defined , and how available , are important aspects of designing an enterprise data storage architecture according to Miguel Vega at IBM .
Businesses should start paying more attention to data storage as part of their data strategy . As I see it , the cooler analytical tools we use to extract insights from data , which is the new natural resource and get most of the love , seem directly responsible for driving business value .
But while they do have an important role to play , they should not get all the credit .
Here are three ways your organisation ’ s data storage system can also actively boost business performance .
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Turbo charged functionality The data storage system is not a passive element of your wider strategy . The functionality of today ’ s platforms makes them an active contributor to the process of analysing information and deciding what to do next . Virtualisation , a part of software defined storage , is one of the most significant features helping to make this happen .
Software defined storage works by pooling numerous physical storage networks together , so these systems and the data they hold can be managed from one central place . Backup and recovery is made faster and easier as a result , providing single unified management layer for your data lakes .
All flash array is one other key feature of a modern high performance storage system . The technology uses silicon memory chips to store data for writing and reading , and is considered an upgrade from the mechanical hard disk drive .
Miguel Vega is Vice President Systems Hardware at IBM Middle East and Africa
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Simple , seamless , scalability
Software defined storage solutions provides open standard access via all of POSIX , NFS , SBM , CFIS , Hadoop , HDFS , Object Storage , OpenStack Swift , to enable seamless data connectivity to applications across private , hybrid or public cloud .
Next , straightforward scalability allows your storage infrastructure to grow as fast or as slow as demand does . The most effective systems provide vertical scalability by including expansion enclosures to be added dynamically , which minimises downtime and the related financial losses .
For big data , analytics unlimited scalability , software defined storage provides the ability to scale with ease allowing you to quickly build , scale up your storage infrastructure to be even faster , more efficient , and more secure . Software defined storage also makes scalability possible when you need to combine an external storage source with your primary system .
When an external disk system is virtualised , its storage capacity inherits the same functionality and usability as your main system .
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Continuous high availability
A data storage system that drives real business value must offer continuous high availability , without down time or any single point of failure .
Automated path failover support recognises a failed command and resends it down an alternate data path , so the application can keep running . There is also redundant hardware , which provides a backup of vital system components should the primary component fail . Alongside this , hot swappable components enable you to replace failed components without shutting down the entire system .
I hope the above clearly demonstrates just how beneficial a dynamic data storage system is , especially as businesses are now in competition to do more with the data they hold . Whether you already have a coherent data strategy or plan to build one , it would be wise to make storage a priority , rather than a secondary feature .
After all , data is a precious commodity in the new cognitive and cloud era , so why would you want to waste it ? Disk based storage systems are not your only option .
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