Poll |
Data Mining (Analytic) tools you used in 2007: [534 voters]
|
The
first (narrow) bar corresponds to the number of votes where the tool
was selected alone, and the second (wide) bar to the number votes where
the tool was select as one among several; Tools are ordered in
descending order of total number of votes |
Commercial Data Mining Software | |
SPSS Clementine |
116, 73 alone or with SPSS |
Salford CART/MARS/TreeNet/RF
|
106, 54 alone |
Excel |
94, 2 alone |
SPSS |
91, 49 alone or with Clementine |
SAS |
80, 8 alone or with SAS E-Miner |
Angoss |
78, 50 alone |
KXEN |
70, 51 alone |
SQL Server |
38, 2 alone |
MATLAB |
30, 1 alone |
SAS E-Miner |
25, 8 alone or with SAS |
Other commercial tools |
21, 0 alone |
Statsoft Statistica |
15, 2 alone |
Insightful Miner/S-Plus |
14, 0 alone |
Oracle DM |
12, 0 alone |
Tiberius |
11, 3 alone |
FairIsaac Model Builder |
3, 2 alone |
Xelopes |
2, 2 alone |
Miner3D |
2, 0 alone |
Bayesia |
2, 0 alone |
Megaputer |
1, 1 alone |
|
your own code |
61, 7 alone |
|
Free Data Mining Software |
Yale |
103, 70 alone |
Weka |
48, 3 alone |
R |
42, 0 alone |
Other free tools |
30, 0 alone |
C4.5/C5.0/See5 |
14, 0 alone |
Orange |
12, 0 alone |
KNIME |
2, 0 alone |
|
For comparison, here are the results of
2006 KDnuggets Poll on Data mining/analytic tools
Comments
data miner, Price versus value
I do not believe that bigger companies buy SAS due to quality,
scalability and usability, but rather on inertia and the belief that if
they pay the most money, they get the best product.
The value of a data mining workbench should be improved productivity
through the use of innovative algorithsm that minimize the modeling
effort.
Data Mining tools were never intended to be used only by statisticians
and computer scientists. Unfortunately, most tools available in the
market today require advanced skills in order to use effectively.
No - I don't want to dumb the user down... But simply adding more,
equally inefficient algorithms into a data mining tool does not make it
a better tool!
Value is based on improved productivity, not another novel algorithm.
(Editor: for fairness, free tools like Weka offer many more
algorithms than commercial tools like SAS or SPSS. In my experience,
companies buy commercial tools for many reasons, including better
interfaces, reliability, ease of use, scalability - rarely just for
more algorithms.)
yangdongzju
I start to use KXEN when i study datamining in zhejiang university.
I think KXEN is very good at Algorithm compare to other tools such as
WEKA,DB miner etc.
Terry Taerum, Cost / Value of information
I think the previous comment about the "Swiss army knife" is a good
one. I suspect though the purchase of a data mining tool is driven as
much by having the "right tool" as the cost of the tool. There is also
the issue of "my language" and "my interface" and "my application" -
which possibly explains why so many data mining applications come out of
existing database and statistical programs (e.g. SQL, ORACLE, SPSS, SAS
to name but a few...). Finally, there is the question of value of
information and cost of information. Information tends to zero. That
is, as it gets olders, as it gets known by others, as it disintegrates,
it becomes less valuable. The cost also tends to zero. And this places
a limit on what should be spent on an application. So in pulling a tool
out of my favorite tool box, the right tool should be the most important
issue from my point of view.
Ross Bettinger, Data Mining Tools
It would be interesting to cluster data mining tool chosen using size
of company (revenue or equivalent measure) because the cost of the tool
may be a factor in its adoption. SAS E-Miner is a Swiss army knife of
capabilities but it costs a bundle, while a more moderately-priced tool
that does not offer as many algorithms or features may be used because
it is more affordable.
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