I'm a college student. Recently i'm just starting my project(Data Mining Software for Enterprise), but i'm not sure what fuctions should i include in this software.

Could anyone help me to give some suggestions of what i need to do and explain what actually Data Mining is and also what its need because i'm not very clear of what Data Mining is.

Hope someone can help me as soon as possible.

Thx!!! And sorry because my english is very weak, so please forgive me if any error in this message.

There is a large amount of high-quality material available for free on the World Wide Web. I have found these search engines to be especially useful:

AlltheWeb (www.alltheweb.com)
Dogpile (www.dogpile.com)
Google (www.google.com)
Teoma (www.teoma.com)
Yahoo! (www.yahoo.com)

Here are some searching tips:

Include "PDF" as a keyword: Documents in Adobe Acrobat format tend to be better written and more polished than the usual stuff found online.

Include phrases such as "course notes", "class readings" or "lecture notes"- these tend to find college professors' Web pages.

Also consider investigating KDnuggets (www.kdnuggets.com) and Citeseer (www.citeseer.com), which is a search engine of technical papers.

Also, here are some titles I recommend:

"Computer Systems That Learn" by Weiss and Kulikowski
"Data Mining" by Witten and Frank
"Data Mining, Concepts and Techniques", by Han and Kamber
"Predictive Data Mining" by Weiss and Indurkhya

Books like these are reviewed in "Will's Technical Book List", which you can find at:

http://will.dwinnell.com/will/willTechnicalPublications.html

Good luck,
Predictor
http://will.dwinnell.com

Thanks a lot, Preditor!!!!

I will try my best to get the information myself.
But i still have a question, what should i include in the data mining software(functionality,what relationship for the database, or what sort of information can be extracted eg. for book retailer).
I'm need to get this all in this week, so....... But at the moment i will try my best effort to find the information myself.

Anyway, thanks for you kindly help!!!!

Which data mining tool best suits a given need depends on a number of factors.

One important factor is the specific analysis which needs to be performed. Broadly, the most common data mining analyses are: 1. classificiation, 2. numeric prediction, 3. clustering (segmentation), 4. anomaly detection and 5. association rules analysis ("market basket analysis"). 1 and 2, above, will be much easier to perform properly if the tool provides appropriate testing procedures (at elast one of: holdout testing, cross-validation, bootstrapping, etc.).

Another major factor in this decision will be the budget for tools, although I'll note that pricetag is not a good indicator of data mining tool quality. There are some relatively inexpensive tools (<US$1,000) which are very capable and some very pricey ones (>US$100,000) which are fairly weak.

My personal opinion is that, for most analysis, multi-tiered (client-server) tools and special conenctions to the database are unnecessary. Commodity desktop computing hardware has enjoyed astronomical growth in power (which continues unabated), and I have built predictive models on 1,000,000+ rows of data using off-the-shelf PCs. Are there some applications which require more than this? Yes, but ordinary, inexpensive PCs serve well for many applications, and more every day as the platform grows in power.

-Predictor
http://will.dwinnell.com

It has so many analyses for data mining(1. classification, 2. numeric prediction, 3. clustering (segmentation), 4. anomaly detection and 5. association rules analysis) you have told about, but sorry i have no idea of what they are.

Colud you please give me some example of what are they?
For classification, is it just to classified the customer into certain groups such as classified by the product that customer usually brought?

It's appreciate if you could tell me some examples of free data mining software(ease to understand and basic) in the market.

Thx!!!

"Classificiation": categorizing items into pre-defined groups.
Credit Card Customers: Will they repay their loans? Yes / No
Companies: Will they go bankrupt within 12 months? Yes / No
OCR: Which letter is this? A / B / C ... X / Y / Z

"Numeric prediction": predicting numeric values.
What will GE's stock price be next week?
How much corn will this mix of fertilizer yield, per acre?

"Clustering" (sometimes called segmentation): Categorizing items into discovered groups.
What are the basic types of customer behavior?

"Anomaly detection": Identification of "unusual" (possibly incorrect) data.

"Association rules analysis ("market basket analysis"): Finding small sets of items which occurr together.
What products are most often purchased together?

Classification and prediction are, by far, the more common data mining fields, with clustering running a distant third.

-Predictor
http://will.dwinnell.com

I&#39;m very thanks for your help..
Now i know what i have to do(at least the basic), but still one question remain.
what is the best suit language:C++,Delphi...or whatever used to develop this data mining software?
Sorry for disturbing you because i&#39;m a newbie in this + very very few resources i can get here(man,books),so this is the only way i could get the resources...

Oh, sorry!!! I have a most important question left.
If i develop this Data Mining Software for the used in marketing, then what should i do in it actually? The data required to be analyzed, the fucntions should included or elsething.
I don't have a clear idea of what to do with a data mining software althought i knew the techniques for data mining.

If you could give me some examples of data mining software it will be better..

I know that this might be too over, but i really really need your help!!!

I have to finish this project at the end of the year by myself, so....

free data warehouse tools and data mining tools

I suggest examining the Software section at KDnuggets, for both free and commercial offerings:

http://www.kdnuggets.com/software/index.html

-Will Dwinnell
http://will.dwinnell.com