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Predicting your storage capacity with analytics

Tim Jones, Technical Specialist, Tintri ANZ | April 12, 2016
Tim Jones from Tintri talks about how predictive analytics in storage will be the next big trend that more and more companies will move towards.

This vendor-written piece has been edited by Executive Networks Media to eliminate product promotion, but readers should note it will likely favour the submitter's approach.

As 2016 gets underway, there are some trends that we're seeing that will continue to gain more popularity as the year progresses.

One of the major challenges for companies and CIOs is the collection and storage of data, and with this, the need for ongoing management and protection. While intelligent applications (Expert Systems) have been on the rise in some areas of technology, the storage market is long overdue in this area. However, we anticipate this will change as we see greater adoption of real-time and predictive storage analytics in Australia and New Zealand in 2016. 

According to analyst group IDC, currently, only 1 percent of all apps use prescriptive analytics. That number is set to rise by 2018 to 50 percent. IDC is predicting that analytics will be embedded in every application, used to facilitate functionality or convenience. 

In today's fast-moving world, business generally requires IT to be proactive and provide more answers, faster. The ability for organisations to have high quality, rich insights into their data usage is extremely valuable and key to forecasting, tracking physical and performance capacity. And this is when predictive analytics come into play; allowing applications to provide a real-time, automated view of the platform landscape, thus saving an organisation copious amounts of time, a task which would normally require hours (if not days) of reporting analysis by information systems experts. These time savings can be better spent by CIOs redirecting IT staff to find new ways to automate data centre tasks.

What does predictive analytics offer?
Predictive analytics can help CIOs take the guesswork out of storage capacity management and receive intuitive and real-time information about their organisation's storage so as to be able to take immediate action and resolve issues quickly to ensure optimum performance.

Stored data is growing - both with Big Data and with normal corporate consumption - where almost no one has in place purge or data obsolescence policies to reduce data growth. As a result, we believe predictive analytics will increasingly be a key component in the development of storage solutions as it offers several advantages which include:

  • Tools for capacity and performance planning. These are imperative for CIOs to be able to forecast and plan in advance for upgrading their storage needs and environment, and ensure adequate lifecycle management for their platform(s).
  • Real-time feedback. For an organisation, knowing what its real-time data consumption is can help it to scale up or scale down its storage needs, making it more agile and better equipped to adapt as needed. This is especially important in today's environment where the identification of which workloads are cloud ready is imperative.
  • Lower cost of ownership. Having the right information when you have to make a decision is important as decisions about infrastructure usually tend to involve spending more money and using more time or resources to ensure the business operates at full capacity..
  • Improvement in the quality of support services. While failure prediction is handy to know, analytics will provide an additional facet to an organisation and allow it to improve the quality of its services.

 

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