3 ms·

Some clarifications. 1. Java and Python are good languages for data mining, due to their libraries, though the others aren't great. C++ is good for finance. 2

by elchief 14y ago

Some clarifications. 1. Java and Python are good languages for data mining, due to their libraries, though the others aren't great. C++ is good for finance. 2. Excel is not a statistical analysis package. "Just because you can drive a car with your feet doesn't make it a good idea" - Chris Rock. Excel is great for pivot tables, however. 3. Hadoop is not a distributed database, it is MapReduce plus a distributed file system. Hive is also not really a distributed database. It lets you write SQL that turns into mapreduce jobs.

jwilliams 14y ago
1. I wouldn't discount Perl. Depending on the industry it can be quite prevalent & it's very common as glue in others.
- elchief 14y ago
  which Perl data mining libraries do you use/recommend?
  - jwilliams 14y ago
    The only one I've ever touched is BioPerl. It's well regarded in the Bioinformatics sphere.
rjdagost 14y ago
Excel is the most common statistical analysis package on the planet, bar-none. When you need to deliver code to people who are numerate but don't program then Excel is the best thing to use. Sometimes you just need to give someone (a manager) a tool where they can test out a bunch of different scenarios but you don't have time to make a polished application. Even for "big data" applications sometimes seeing the numbers in front of you in cells is quite useful.
- elchief 14y ago
  Yes, it is popular, but that doesn't make it good for statistical analysis. It also sucks compared to JMP. On the accuracy of statistical procedures in Microsoft Excel 2007 http://or.nps.edu/faculty/PaulSanchez/oa4333/handouts/Excel/excel2007.pdf http://or.nps.edu/faculty/PaulSanchez/oa4333/handouts/Excel/...
berkeleyjess 14y ago
Thanks for the corrections. I have changed the post to reflect the Hadoop/Hive/MapReduce mistake. I am still new at this tech thing and obviously don't know all the terminology yet.
- elchief 14y ago
  No worries, thanks for the post!

by elchief 14y ago

jwilliams 14y ago

1. I wouldn't discount Perl. Depending on the industry it can be quite prevalent & it's very common as glue in others.

elchief 14y ago
which Perl data mining libraries do you use/recommend?
- jwilliams 14y ago
  The only one I've ever touched is BioPerl. It's well regarded in the Bioinformatics sphere.

rjdagost 14y ago

Excel is the most common statistical analysis package on the planet, bar-none. When you need to deliver code to people who are numerate but don't program then Excel is the best thing to use. Sometimes you just need to give someone (a manager) a tool where they can test out a bunch of different scenarios but you don't have time to make a polished application. Even for "big data" applications sometimes seeing the numbers in front of you in cells is quite useful.

elchief 14y ago
Yes, it is popular, but that doesn't make it good for statistical analysis. It also sucks compared to JMP. On the accuracy of statistical procedures in Microsoft Excel 2007 http://or.nps.edu/faculty/PaulSanchez/oa4333/handouts/Excel/excel2007.pdf http://or.nps.edu/faculty/PaulSanchez/oa4333/handouts/Excel/...

berkeleyjess 14y ago

Thanks for the corrections. I have changed the post to reflect the Hadoop/Hive/MapReduce mistake. I am still new at this tech thing and obviously don't know all the terminology yet.

elchief 14y ago
No worries, thanks for the post!