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The Vs for Data

Data is the most challenging aspect in today’s data-driven world. Our data is frequently incomplete, dirty, corrupted, or in some rare circumstances not collected at all. Preparing data for the work of data science or artificial intelligent use takes the bulk of work not the data science. The common the six Vs are just the beginning of data management, they are absolutely necessary considerations i.e. volume, velocity, variety, veracity, value and variability. Which other “V” is worth considering when dealing with data ?

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