Which is the most useful and easy to learn data analysis tool?

I tried PAW, but is there anything better?

Thanks in advance.

asked 21 Mar '11, 03:34

Ram's gravatar image

accept rate: 0%

edited 19 Feb '12, 11:32

fbahr's gravatar image

fbahr ♦

Here are the tools that may help you analyze your data:

Machine Learning and Data Mining Tools

  • Weka
  • Google Prediction API
  • Orange (and many other python libraries for AL and Machine Learning)
  • Apache Mahout (Thanks to Geoffrey De Smet) intro video
  • R is also capable of doing many machine learning tasks see this page (H/T larrydag)

Statistical Tools

  • SAS
  • R
  • Excel
  • Stata

Tools for exploratory data analysis

  • Tablau is a great tool but you need to pay for it
  • ggobi, and ggplot2
  • Excel
  • Protoviz and Flare

answered 22 Mar '11, 07:10

Mark's gravatar image

Mark ♦
accept rate: 9%

edited 22 Mar '11, 21:44


Another machine learning tool is Apache Mahout.

(22 Mar '11, 09:10) Geoffrey De ... ♦

R is great for machine learning as well. http://cran.r-project.org/web/views/MachineLearning.html

(22 Mar '11, 12:43) larrydag 1 ♦

definitevely R (not the simplest, but on the long term you'll never regret it).


answered 21 Mar '11, 12:19

pierre%20schaus's gravatar image

pierre schaus
accept rate: 4%

I couldn't agree more. Here is a blog post I did for R Beginners. http://industrialengineertools.blogspot.com/2010/10/r-links-for-beginner-on-world.html

(21 Mar '11, 12:35) larrydag 1 ♦

If "data analysis" = "statistical analysis", I agree that R is a good choice. If "data analysis" = "data mining", I'd probably look at RapidMiner or Weka. You can do a fair bit of data mining in R, but RapidMiner and Weka are easier to learn.


answered 21 Mar '11, 15:46

Paul%20Rubin's gravatar image

Paul Rubin ♦♦
accept rate: 19%

I generally assume everybody knows excel (might be a bad assumption). If you don't know excel, start there. Excel has the VB scripting language which is pretty easy to pick up to do more complicated data mashing, and lots of built in functionality to make it easy to deal with dates, sequences, series and formulas. Excel has basic statistical analysis built in, histograms, regression, standard deviation etc. You can do linear programming problems in excel and graphing is really easy. Pivot table functionality in excel is invaluable (seriously, I don't know what I would do without pivot tables). I've settled on a combo of tools for my professional life: SAS (to prepare and clean data), R (to do analysis and graphing) and Excel for smaller problems or problems with lots of little pieces and parts that become overly cumbersome to load into SAS or R data structures.


answered 23 Feb '12, 17:49

austinboston's gravatar image

accept rate: 0%

IANAE, but whenever someone mentions Excel I feel compelled to add: Excel is well-known for its computational inaccuracies (of all kinds) since, well, ever. And little has changed since then, e.g. Floating-point arithmetic may give inaccurate results in Excel.

(24 Feb '12, 06:23) fbahr ♦

I've never really looked into that, very interesting. Thanks.

(02 Mar '12, 17:36) austinboston
Your answer
toggle preview

Follow this question

By Email:

Once you sign in you will be able to subscribe for any updates here



Answers and Comments

Markdown Basics

  • *italic* or _italic_
  • **bold** or __bold__
  • link:[text](http://url.com/ "Title")
  • image?![alt text](/path/img.jpg "Title")
  • numbered list: 1. Foo 2. Bar
  • to add a line break simply add two spaces to where you would like the new line to be.
  • basic HTML tags are also supported



Asked: 21 Mar '11, 03:34

Seen: 6,903 times

Last updated: 02 Mar '12, 17:36

OR-Exchange! Your site for questions, answers, and announcements about operations research.