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Simplifying Big Data Projects with Data Virtualization
According to Gartner, 60% of all the big data projects fail and according to Capgemini 70% of the big data projects are not profitable. There can only be one conclusion, big data projects are hard! There is not one specific reason for this situation, but many. For example, some big data storage and processing technologies are complex to use, for most IT specialists the technology is new, and sometimes big data products are used for the wrong use case.Despite these disappointing results, organizations still initiate big data projects in order to take advantage of the potential business benefits promised by the big data proponents.Data virtualization can help to simplify big data projects. It won’t solve all the problems, but if deployed for the right use cases, it will definitely increase the likelihood that big data projects succeed. Here are some examples of proper use cases.Massive amounts of big data are stored in plain files. This makes it hard for non-tech-savvy business users to access it. Data virtualization servers can hide this complexity and can make big data available to a larger business audience and to many popular BI tools. They do encapsulate big data through a simple virtual table that can easily be accessed.
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