IDC predicts that converged infrastructure will transition from market hype to market reality in 2013. Barun Lala, director-Storage at HP India, spoke about HP’s innovations in its converged storage portfolio.
HP first announced the Converged Storage portfolio in 2011, and then expanded its storage offering in December 2012. What do you think has changed in the last one year in terms of data, storage and other related aspects?
It was the end of 2010 when HP introduced the concept of what is now known as "converged infrastructure". Converged infrastructure is supported by five important pillars: Virtualization, resilience, optimization, orchestration, and modularity. Later, IDC predicted that these five requirements would eventually become a standard. So when most of the companies adopted virtualization as a standard, HP, in 2011, announced the concept of converged storage, whose basic purpose is to reduce the complexity and inefficiency existing in the customer environment. For example, a couple of years ago, most of us had just basic mobile phones, not smartphones. Recent reports suggest that today, a majority of people in India who are less than 25 years of age are smartphone users. Similarly, the volume of structured data generated was high earlier. Today, due to the widespread usage of social media, more and more unstructured data is being generated. Therefore, companies require advanced technologies in order to manage data in a simpler format. Customers need to be able to save costs in operations and invest them in innovation.
With the advent of big data, storage has become one of the primary concerns for CIOs. What are some of the challenges CIOs face when it comes to IT management?
Customers' challenges vary depending upon the vertical they operate in. For example, the primary business challenge for a leading PSU in the natural resource sector was converting the large quantities of its analog data to digital format. In the telecom vertical, one of the major concerns is to perform a deep-dive analysis on the telecom usage of their clientele--for instance, evaluating the average telecom bill of a particular subscriber. They might have a huge database of customers, but if they analyze deeply, they will infer that only 10-15 percent of customers use the various value-added services offered by them on their network. It's very clear that if a customer does not use these services, the telecom provider is actually making a loss per subscriber. Therefore, they require a high-end tool to carry out the analytics. So, there's a host of big data challenges and they differ according to the industry.
According to IDC, storage is estimated to account for 37 percent of the total energy consumed in today's datacenters. What are some of the parameters contributing to the decision-making cycle of a customer?
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