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0 pointsgaius14y ago0 comments

Right, but BAs have been doing SPSS, SAS, Mathematica, MATLAB, R etc, etc for decades. Any BA worth his or her salt could pick up these new things without breaking a sweat - they are not rocket science, and the value of a BA is in their knowledge of statistics and industry domain knowledge.

A DS is a BA without sufficient industry experience to know there is already a job doing what they do...

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yummyfajitas14y ago

I don't really agree with this. A "Data Scientist" (as the term is "properly" used [1]) generally needs to be a very good computer scientist in addition to understanding the data.

Ordinary data analysis generally lives in a world where the computer is fast enough, and you need domain knowledge + basic stats. The term "Data Scientist", when properly used, deals with cases where domain knowledge + basic stats isn't sufficient, and computer science knowledge is also required.

[1] Many people who advertise for a "data scientist" really just need a BA or a DBA. I recently turned down a job as a "data scientist" after telling them that Hadoop is massive overkill. `SELECT SUM(x) FROM table WHERE condition` took about 4 seconds to run. Admittedly, the ruby script they were using to do it row by row was a lot slower, particularly since they were loading the entire row rather than just field `x`.

dbecker14y ago

Different people mean different things by the BA/DS distinction. But I've seen a team of 15 people with SAS experience try to get into machine learning applications, and they are making less progress than I would expect from a single good ML practitioner (with R or Python experience).

This is just an anecdote... And Perhaps some people make the BA/DS distinction so this isn't the relevant comparison. But the returns to smart people and sharp tools is astounding.

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