After an intro ad, Stonebreaker gives the semi-common "3 V's" definition of big data of "volume, velocity, variety" popularized by META/Gartner [0]. And then he talks briefly about using big data for integration from many data sources, and then he concludes by relaying the interest that the Miller Beer company expressed in knowing the relationship between El Nino / temperature / precipitation and sales of beer.
Stonebraker is pretty sharp but you would never know it from this bit of puff.
Here is a much better talk by him, but its a bit dated, however if you have never spent much time thinking about real "big data" its a great introduction.
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[ 4.2 ms ] story [ 16.4 ms ] threadCan someone post a transcript or the gist of his message?
Volume - you have too much data, Velocity - it's coming at you too fast, Variety - it's coming from too many different places,
But then he goes on to talk about specifics and gets strangely cut off.
"Are beer sales affected by weather?" is an example of a question that is solved by Variety, which is the the last concept he was talking about.
After an intro ad, Stonebreaker gives the semi-common "3 V's" definition of big data of "volume, velocity, variety" popularized by META/Gartner [0]. And then he talks briefly about using big data for integration from many data sources, and then he concludes by relaying the interest that the Miller Beer company expressed in knowing the relationship between El Nino / temperature / precipitation and sales of beer.
[0] https://en.wikipedia.org/wiki/Big_data#Definition
Here is a much better talk by him, but its a bit dated, however if you have never spent much time thinking about real "big data" its a great introduction.
https://www.youtube.com/watch?v=OYGJe1z97VI