The twelve days of big data analytics

8

datascientist_dtreeOn 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.

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About Author

David Pope

Technical Leader, Senior Manager US Energy

David leads the pre-sales technical team for SAS US Energy which solves business problems in the Oil & Gas and Utilities industries using advanced analytics. He earned a BS in Industry Engineering and a Computer Programming Certificate from North Carolina State University. Furthermore, he has over 27 years of business experience working with SAS across R&D, IT, Sales and Marketing in the Americas and Europe. He is an expert in working with data and producing insights through the use of analytics. David has presented at SAS Global Forum, the 2012 SAS Government Leadership Summit, IBM’s Information on Demand(IOD), EMC World, CTO Summit Conferences, is the author of the book: "Big Data Analytics with SAS", and he currently holds 11 patents for SAS in several countries: US, CA, Norway, UK, China, and Hong Kong.

8 Comments

    • David Pope

      Now you will have to ponder what if any hidden meaning there is between business colleagues vs colleagues and/or vendors 🙂

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