Big data has become integral to the continued development of companies in many sectors over the last several years. Whether it's for identifying improvement opportunities in supply chain management, targeting customers with more effective marketing, or improving the company Web presence for optimal business-to-business interactivity, massive quantities of information are driving decision making like never before. Scalable enterprise IaaS clouds offer organizations opportunities to better position themselves for evolution within the big data paradigm without missing a beat.

Organizations are increasingly turning to unstructured data streams for dynamic, creative insights. Unlike systematical data sources, like customer surveys and databases, where information is laid out, organized and easily drawn from, unstructured data currents, like social media conversations and audio transcripts, are those in which learned machines must parse through reams of content in order to extract gold nuggets of insight. This phenomenon increases the need for infrastructure solutions that not only support massive amounts of data storage, but can optimize system and network capacities for complex, automated data processing schemes.

Where IaaS clouds and big data converge
Few companies have legacy infrastructure that can support their current big data needs, let alone the ever-expanding sea of information looming on the horizon. For many organizations, the virtualization of their big data platforms has reached a fever pitch. This reality likely necessitates further overlap between enterprise IaaS clouds and big data management, wrote Forbes contributor Edward Newman. In environments where virtual machines could number in the thousands, understanding how these resources are stored in data centers is important for big data functionality.

Understanding how data works leads to better protection as well, according to the Guardian contributor Richard Moulds. While a majority of organizations have indicated their plans to transfer confidential information to cloud storage, some are worried that doing so will increase the pressure placed on IT. Ultimately, this sentiment stems from not having a clear picture of how IaaS clouds work and how data is archived and accessed. Companies that understand big data will be better situated to classify it. Then they can control access and security from the cloud on a granular level, determining who has access to what and implementing real-time updates to that system. Additionally, organizations can work with their cloud service provider to decide whether to store encryption keys on premises or in the cloud, providing an extra tier of security according to their specific needs.

"Confidence in the cloud depends on understanding your data," Moulds wrote. "What is it? Where does it need to be protected? And what level of protection does it require? Failure to understand your organization's data pyramid is to put valuable business assets at risk. Only you know what your data is worth."