Big Data Volume, Variety, Velocity and Veracity

Big Data Volume, Variety, Velocity and Veracity

The SIG Resource Center is moving to The SIG Community. If you are a SIG Member, or enrolled in SIG University, and don’t have access yet, you can do so here. Already have access? Log in and visit the new SIG Resource Center.

Resource Origin: inside BIG DATA

“We have all heard of the the 3Vs of big data which are Volume, Variety and Velocity. Yet, Inderpal Bhandar, Chief Data Officer at Express Scripts noted in his presentation at the Big Data Innovation Summit in Boston that there are additional Vs that IT, business and data scientists need to be concerned with, most notably big data Veracity. Other big data V’s getting attention at the summit are: validity and volatility. Here is an overview the 6V’s of big data. Volume Big data implies enormous volumes of data. It used to be employees created data. Now that data is generated by machines, networks and human interaction on systems like social media the volume of data to be analyzed is massive. Yet, Inderpal states that the volume of data is not as much the problem as other V’s like veracity. Variety Variety refers to the many sources and types of data both structured and unstructured. We used to store data from sources like spreadsheets and databases. Now data comes in the form of emails, photos, videos, monitoring devices, PDFs, audio, etc. This variety of unstructured data creates problems for storage, mining and analyzing data. Jeff Veis, VP Solutions at HP Autonomy presented how HP is helping organizations deal with big challenges including data variety…”

https://insidebigdata.com/2013/09/12/beyond-volume-variety-velocity-issue-big-data-veracity/

Contributors:
Categories: ,
SRC Type: ,

Please log in to download the document.

Please log in to view the video.