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Data storage has become a predicament for corporations and small-and-medium-sized businesses alike. On-premise storage infrastructure leveraged by a company for the exponential amount of data created oftentimes proves to be costly with low return on investment. The on-premise locations have to take care of servers, find large spaces with good ventilation and cooling systems to maintain a data center, as well as hire data experts to maintain the server machines. Not to mention the storage of excessive structured and unstructured data means the IT team have to keep track of the space used in storage and constantly eliminate the unnecessary data right away to provide free storage for the necessary data.
Currently, most of the companies are willing to transfer their data to the public cloud by adopting infrastructure-as-a-service. This not only reduces expenditure but also increases the productivity of the existing data scientists of the company as they can focus on other essential tasks. Moreover, the public cloud servers such as the Amazon cloud, Microsoft Azure, and Google cloud are designed to retrieve and save data in several remote locations to prevent information loss due to server failure. In fact, Google is on the verge of re-designing its cloud by transforming the disk drive to reduce the cost and increase the storage capacity of data alongside low maintenance.