5 Ways to Mitigate Costs Associated with Machine Data

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5 Ways to Mitigate Costs Associated with Machine Data

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When a term like the Internet of Things, or IoT, is used as frequently as it has been in recent years, it's tempting to write off the concept as a buzzword. Companies know that it ties into their work, but unless they're involved in a few specific industries, they may not think it directly affects their daily operations.

This kind of assumption couldn't be farther from the truth. IoT data encompasses log and machine data and it's produced constantly — by the servers, networks, security systems and sensors that you might expect, but also by the applications managing enterprise, security and operational analytics. IDC predicts that 42 percent of all data will be machine generated by 2020. As this data grows rapidly, many organizations are discovering that yesterday's storage systems weren't built to handle machine data.

To keep up with machine data growth and avoid costs it traditionally incurs, such as scaling physical hardware and dealing with cloud access fees, companies need to combine on-premises storage performance and availability with the elasticity and economics of the cloud. In this slideshow, Ellen Rubon, CEO and co-founder of ClearSky Data, has identified five ways organizations can make the best of both worlds a reality for their team.

Ellen Rubin is the CEO and co-founder of ClearSky Data. She is an experienced entrepreneur with a record in leading strategy, market positioning and go-to market efforts for fast-growing companies. ClearSky Data's global storage network simplifies the entire data lifecycle and delivers enterprise storage as a fully managed service. Most recently, Ellen was co-founder of CloudSwitch, a cloud-enablement software company that was acquired by Verizon in 2011.