Stonebraker Breaks down Big Data in 90 Seconds (2013) [video](bizjournals.com)
bizjournals.com
Stonebraker Breaks down Big Data in 90 Seconds (2013) [video]
http://www.bizjournals.com/boston/blog/startups/2013/03/michael-stonebraker-what-is-big-data.html
4 comments
He's making a business case for his company http://www.tamr.com :)
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.
https://www.youtube.com/watch?v=OYGJe1z97VI
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
Video does not play on either Firefox of Chrome.
Can someone post a transcript or the gist of his message?
Can someone post a transcript or the gist of his message?
Basically says big data = three Vs.
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.
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.
It was cut that way on purpose.
"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.
"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