On the first day of Big Data Analytics
my colleagues sent to me:
A data scientist discussing a decision tree

On the second day of Big Data Analytics
my colleagues sent to me:
Two business analysts and
A data scientist discussing a decision tree

On the third day of Big Data Analytics
my colleagues sent to me:
Three different regressions (step-wise, forward and backwards  selection)
Two business analysts and
A data scientist discussing a decision tree

On the fourth day of Big Data Analytics
my colleagues sent to me:
Four random forests
Three different regressions (step-wise, forward and backwards  selection)
Two business analysts and
A data scientist discussing a decision tree

On the fifth day of Big Data Analytics
my colleagues sent to me:
Five time series
Four random forests
Three different regressions (step-wise, forward and backwards  selection)
Two business analysts and
A data scientist discussing a decision tree

On the sixth day of Big Data Analytics
my colleagues sent to me:
Six k-means a-clustering
Five time series
Four random forests
Three different regressions (step-wise, forward and backwards  selection)
Two business analysts and
A data scientist discussing a decision tree

On the seventh day of Big Data Analytics
my colleagues sent to me:
Seven linear programs a-optimizing
Six k-means a-clustering
Five time series
Four random forests
Three different regressions (step-wise, forward and backwards  selection)
Two business analysts and
A data scientist discussing a decision tree

On the eighth day of Big Data Analytics
my colleagues sent to me:
Eight ARIMAs a-forecasting
Seven linear programs a-optimizing
Six k-means a-clustering
Five time series
Four random forests
Three different regressions (step-wise, forward and backwards  selection)
Two business analysts and
A data scientist discussing a decision tree

On the ninth day of Big Data Analytics
my colleagues sent to me:
Nine neural networks a-processing
Eight ARIMAs a-forecasting
Seven linear programs a-optimizing
Six k-means a-clustering
Five time series
Four random forests
Three different regressions (step-wise, forward and backwards  selection)
Two business analysts and
A data scientist discussing a decision tree

On the tenth day of Big Data Analytics
my colleagues sent to me:
Ten VPs a-leaping
Nine neural networks a-processing
Eight ARIMAs a-forecasting
Seven linear programs a-optimizing
Six k-means a-clustering
Five time series
Four random forests
Three different regressions (step-wise, forward and backwards  selection)
Two business analysts and
A data scientist discussing a decision tree

On the eleventh day of Big Data Analytics
my colleagues sent to me:
Eleven data streams a-streaming
Ten VPs a-leaping
Nine neural networks a-processing
Eight ARIMAs a-forecasting
Seven linear programs a-optimizing
Six k-means a-clustering
Five time series
Four random forests
Three different regressions (step-wise, forward and backwards  selection)
Two business analysts and
A data scientist discussing a decision tree

On the twelfth day of Big Data Analytics
my business colleagues sent to me:
Twelve vendors selling
Eleven data streams a-streaming
Ten VPs a-leaping
Nine neural networks a-processing
Eight ARIMAs a-forecasting
Seven linear programs a-optimizing
Six k-means a-clustering
Five time series
Four random forests
Three different regressions (step-wise, forward and backwards  selection)
Two business analysts and
A data scientist discussing a decision tree

Now that we had some fun, you'll probably want to find out more about big data analytics, for example: why is big data analytics important? Or perhaps you're more interested in exploring hot topics in analytics like: data mining or machine learning.