Stanford Seminar - Big Data Is -At Least- Four Different Problems

Explore the multifaceted nature of Big Data in this Stanford seminar, delving into four distinct challenges: volume, velocity, variety, and veracity. Learn about data science templates, complex analytics on array data, and the evolution of Hadoop. Examine various approaches to handling high-velocity data streams and the importance of data integration at scale. Discover emerging solutions like data lakes and startups tackling Big Data challenges. Gain insights into the future of complex analytics, including Spark and R, while considering potential obstacles in the field. Understand the significance of data curation and the absence of a global data model in addressing Big Variety issues.

Introduction.
The Meaning of Big Data - 3 V's.
Big Volume - Little Analytics.
The Big Disruption.
Data Science Template.
Complex Analytics on Array Data - An Accessible Example.
Array Answer.
st option).
Map-Reduce.
The Future of Hadoop.
nd option -- 2015).
rd option).
th option).
The Future of Complex Analytics, Spark, R, and .....
Big Velocity - 2nd Approach.
In My Opinion.....
Possible Storm Clouds.
Big Variety.
Traditional Solution -- ETL.
And there is NO Global Data Model.
Why Integrate Silos?.
Why is Data Integration Hard?.
Data Integration (Curation) AT SCALE is a VERY Big Deal.
A Bunch of Startups With New Ideas.
To Achieve Scalability.....
Data Lakes.
Take away.