Many vendors and pundits have attempted to augment Gartner’s original “3Vs” from the late 1990s with clever(?) “V”s of their own. However, the 3Vs were intended to define the proportional dimensions and challenges specific to big data. Other “V”s like veracity, validity, value, viability, etc. are aspirational qualities of all data, not definitional qualities of big data. Conflating inherent aspects with important objectives leads to poor prioritization and planning. For example, if you’re like many organizations, your terabytes of streamed sensor, log file or multimedia data may not have veracity (data quality) issues at all, but your megabytes of master data may be in total disarray.
As author and analytics strategy consultant Seth Grimes observes in his InformationWeek piece Big Data: Avoid ‘Wanna V’ Confusion, “When a concept resonates, as big data has, vendors, pundits and gurus — the revisionists — spin it for their own ends….In my opinion, the wanna-V backers and the contrarians mistake interpretive, derived qualities for essential attributes.”
Also follow Doug on Twitter @Doug_Laney
Comments or opinions expressed on this blog are those of the individual contributors only, and do not necessarily represent the views of Gartner, Inc. or its management. Readers may copy and redistribute blog postings on other blogs, or otherwise for private, non-commercial or journalistic purposes, with attribution to Gartner. This content may not be used for any other purposes in any other formats or media. The content on this blog is provided on an "as-is" basis. Gartner shall not be liable for any damages whatsoever arising out of the content or use of this blog.