Web Scraper Shortcode WordPress Plugin Review

This short post is on the WP-plugin called Web Scraper Shortcode, that enables one to retrieve a portion of a web page or a whole page and insert it directly into a post. This plugin might be used for getting fresh data or images from web pages for your WordPress driven page without even visiting it. More scraping plugins and sowtware you can find in here.

To install it in WordPress go to Plugins -> Add New.
Usage

The plugin scrapes the page content and applies parameters to this scraped page if specified. To use the plugin just insert the

[web-scraper ]

shortcode into the HTML view of the WordPress page where you want to display the excerpts of a page or the whole page. The parameters are as follows:

    url (self explanatory)
    element – the dom navigation element notation, similar to XPath.
    limit – the maximum number of elements to be scraped and inserted if the element notation points to several of them (like elements of the same class).

The use of the plugin is of the dom (Data Object Model) notation, where consecutive dom nodes are stated like node1.node2; for example: element = ‘div.img’. The specific element scrape goes thru ‘#notation’. Example: if you want to scrape several ‘div’ elements of the class ‘red’ (<div class=’red’>…<div>), you need to specify the element attribute this way: element = ‘div#red’.
How to find DOM notation?

But for inexperienced users, how is it possible to find the dom notation of the desired element(s) from the web page? Web Developer Tools are a handy means for this. I would refer you to this paragraph on how to invoke Web Developer Tools in the browser (Google Chrome) and select a single page element to inspect it. As you select it with the ‘loupe’ tool, on the bottom line you’ll see the blue box with the element’s dom notation:


The plugin content

As one who works with web scraping, I was curious about  the means that the plugin uses for scraping. As I looked at the plugin code, it turned out that the plugin acquires a web page through ‘simple_html_dom‘ class:

    require_once(‘simple_html_dom.php’);
    $html = file_get_html($url);
    then the code performs iterations over the designated elements with the set limit

Pitfalls

    Be careful if you put two or more [web-scraper] shortcodes on your website, since downloading other pages will drastically slow the page load speed. Even if you want only a small element, the PHP engine first loads the whole page and then iterates over its elements.
    You need to remember that many pictures on the web are indicated by shortened URLs. So when such an image gets extracted it might be visible to you in this way: , since the URL is shortened and the plugin does not take note of  its base URL.
    The error “Fatal error: Call to a member function find() on a non-object …” will occur if you put this shortcode in a text-overloaded post.

Summary

I’d recommend using this plugin for short posts to be added with other posts’ elements. The use of this plugin is limited though.



Source: http://extract-web-data.com/web-scraper-shortcode-wordpress-plugin-review/

Visual Web Ripper: Using External Input Data Sources

Sometimes it is necessary to use external data sources to provide parameters for the scraping process. For example, you have a database with a bunch of ASINs and you need to scrape all product information for each one of them. As far as Visual Web Ripper is concerned, an input data source can be used to provide a list of input values to a data extraction project. A data extraction project will be run once for each row of input values.

An input data source is normally used in one of these scenarios:

    To provide a list of input values for a web form
    To provide a list of start URLs
    To provide input values for Fixed Value elements
    To provide input values for scripts

Visual Web Ripper supports the following input data sources:

    SQL Server Database
    MySQL Database
    OleDB Database
    CSV File
    Script (A script can be used to provide data from almost any data source)

To see it in action you can download a sample project that uses an input CSV file with Amazon ASIN codes to generate Amazon start URLs and extract some product data. Place both the project file and the input CSV file in the default Visual Web Ripper project folder (My Documents\Visual Web Ripper\Projects).

For further information please look at the manual topic, explaining how to use an input data source to generate start URLs.


Source: http://extract-web-data.com/visual-web-ripper-using-external-input-data-sources/

Using External Input Data in Off-the-shelf Web Scrapers

There is a question I’ve wanted to shed some light upon for a long time already: “What if I need to scrape several URL’s based on data in some external database?“.

For example, recently one of our visitors asked a very good question (thanks, Ed):

    “I have a large list of amazon.com asin. I would like to scrape 10 or so fields for each asin. Is there any web scraping software available that can read each asin from a database and form the destination url to be scraped like http://www.amazon.com/gp/product/{asin} and scrape the data?”

This question impelled me to investigate this matter. I contacted several web scraper developers, and they kindly provided me with detailed answers that allowed me to bring the following summary to your attention:
Visual Web Ripper

An input data source can be used to provide a list of input values to a data extraction project. A data extraction project will be run once for each row of input values. You can find the additional information here.
Web Content Extractor

You can use the -at”filename” command line option to add new URLs from TXT or CSV file:

    WCExtractor.exe projectfile -at”filename” -s

projectfile: the file name of the project (*.wcepr) to open.
filename – the file name of the CSV or TXT file that contains URLs separated by newlines.
-s – starts the extraction process

You can find some options and examples here.
Mozenda

Since Mozenda is cloud-based, the external data needs to be loaded up into the user’s Mozenda account. That data can then be easily used as part of the data extracting process. You can construct URLs, search for strings that match your inputs, or carry through several data fields from an input collection and add data to it as part of your output. The easiest way to get input data from an external source is to use the API to populate data into a Mozenda collection (in the user’s account). You can also input data in the Mozenda web console by importing a .csv file or importing one through our agent building tool.

Once the data is loaded into the cloud, you simply initiate building a Mozenda web agent and refer to that Data list. By using the Load page action and the variable from the inputs, you can construct a URL like http://www.amazon.com/gp/product/%asin%.
Helium Scraper

Here is a video showing how to do this with Helium Scraper:


The video shows how to use the input data as URLs and as search terms. There are many other ways you could use this data, way too many to fit in a video. Also, if you know SQL, you could run a query to get the data directly from an external MS Access database like
SELECT * FROM [MyTable] IN "C:\MyDatabase.mdb"

Note that the database needs to be a “.mdb” file.
WebSundew Data Extractor
Basically this allows using input data from external data sources. This may be CSV, Excel file or a Database (MySQL, MSSQL, etc). Here you can see how to do this in the case of an external file, but you can do it with a database in a similar way (you just need to write an SQL script that returns the necessary data).
In addition to passing URLs from the external sources you can pass other input parameters as well (input fields, for example).
Screen Scraper

Screen Scraper is really designed to be interoperable with all sorts of databases. We have composed a separate article where you can find a tutorial and a sample project about scraping Amazon products based on a list of their ASINs.


Source: http://extract-web-data.com/using-external-input-data-in-off-the-shelf-web-scrapers/

Selenium IDE and Web Scraping

Selenium is a browser automation framework that includes IDE, Remote Control server and bindings of various flavors including Java, .Net, Ruby, Python and other. In this post we touch on the basic structure of the framework and its application to  Web Scraping.
What is Selenium IDE


Selenium IDE is an integrated development environment for Selenium scripts. It is implemented as a Firefox plugin, and it allows recording browsers’ interactions in order to edit them. This works well for software tests, composing and debugging. The Selenium Remote Control is a server specific for a particular environment; it causes custom scripts to be implemented for controlled browsers. Selenium deploys on Windows, Linux, and iOS. How various Selenium components are supported with major browsers read here.
What does Selenium do and Web Scraping

Basically Selenium automates browsers. This ability is no doubt to be applied to web scraping. Since browsers (and Selenium) support JavaScript, jQuery and other methods working with dynamic content why not use this mix for benefit in web scraping, rather than to try to catch Ajax events with plain code? The second reason for this kind of scrape automation is browser-fasion data access (though today this is emulated with most libraries).

Yes, Selenium works to automate browsers, but how to control Selenium from a custom script to automate a browser for web scraping? There are Selenium PHP and other language libraries (bindings) providing for scripts to call and use Selenium. It is possible to write Selenium clients (using the libraries) in almost any language we prefer, for example Perl, Python, Java, PHP etc. Those libraries (API), along with a server, the Java written server that invokes browsers for actions, constitute the Selenum RC (Remote Control). Remote Control automatically loads the Selenium Core into the browser to control it. For more details in Selenium components refer to here.


A tough scrape task for programmer

“…cURL is good, but it is very basic.  I need to handle everything manually; I am creating HTTP requests by hand.
This gets difficult – I need to do a lot of work to make sure that the requests that I send are exactly the same as the requests that a browser would
send, both for my sake and for the website’s sake. (For my sake
because I want to get the right data, and for the website’s sake
because I don’t want to cause error messages or other problems on their site because I sent a bad request that messed with their web application).  And if there is any important javascript, I need to imitate it with PHP.
It would be a great benefit to me to be able to control a browser like Firefox with my code. It would solve all my problems regarding the emulation of a real browser…
it seems that Selenium will allow me to do this…” -Ryan S

Yes, that’s what we will consider below.
Scrape with Selenium

In order to create scripts that interact with the Selenium Server (Selenium RC, Selenium Remote Webdriver) or create local Selenium WebDriver script, there is the need to make use of language-specific client drivers (also called Formatters, they are included in the selenium-ide-1.10.0.xpi package). The Selenium servers, drivers and bindings are available at Selenium download page.
The basic recipe for scrape with Selenium:

    Use Chrome or Firefox browsers
    Get Firebug or Chrome Dev Tools (Cntl+Shift+I) in action.
    Install requirements (Remote control or WebDriver, libraries and other)
    Selenium IDE : Record a ‘test’ run thru a site, adding some assertions.
    Export as a Python (other language) script.
    Edit it (loops, data extraction, db input/output)
    Run script for the Remote Control

The short intro Slides for the scraping of tough websites with Python & Selenium are here (as Google Docs slides) and here (Slide Share).
Selenium components for Firefox installation guide

For how to install the Selenium IDE to Firefox see  here starting at slide 21. The Selenium Core and Remote Control installation instructions are there too.
Extracting for dynamic content using jQuery/JavaScript with Selenium

One programmer is doing a similar thing …

1. launch a selenium RC (remote control) server
2. load a page
3. inject the jQuery script
4. select the interested contents using jQuery/JavaScript
5. send back to the PHP client using JSON.

He particularly finds it quite easy and convenient to use jQuery for
screen scraping, rather than using PHP/XPath.
Conclusion

The Selenium IDE is the popular tool for browser automation, mostly for its software testing application, yet also in that Web Scraping techniques for tough dynamic websites may be implemented with IDE along with the Selenium Remote Control server. These are the basic steps for it:

    Record the ‘test‘ browser behavior in IDE and export it as the custom programming language script
    Formatted language script runs on the Remote Control server that forces browser to send HTTP requests and then script catches the Ajax powered responses to extract content.

Selenium based Web Scraping is an easy task for small scale projects, but it consumes a lot of memory resources, since for each request it will launch a new browser instance.



Source: http://extract-web-data.com/selenium-ide-and-web-scraping/

Basics of Web Data Mining and Challenges in Web Data Mining Process

Today World Wide Web is flooded with billions of static and dynamic web pages created with programming languages such as HTML, PHP and ASP. Web is great source of information offering a lush playground for data mining. Since the data stored on web is in various formats and are dynamic in nature, it's a significant challenge to search, process and present the unstructured information available on the web.

Complexity of a Web page far exceeds the complexity of any conventional text document. Web pages on the internet lack uniformity and standardization while traditional books and text documents are much simpler in their consistency. Further, search engines with their limited capacity can not index all the web pages which makes data mining extremely inefficient.

Moreover, Internet is a highly dynamic knowledge resource and grows at a rapid pace. Sports, News, Finance and Corporate sites update their websites on hourly or daily basis. Today Web reaches to millions of users having different profiles, interests and usage purposes. Every one of these requires good information but don't know how to retrieve relevant data efficiently and with least efforts.

It is important to note that only a small section of the web possesses really useful information. There are three usual methods that a user adopts when accessing information stored on the internet:

• Random surfing i.e. following large numbers of hyperlinks available on the web page.
• Query based search on Search Engines - use Google or Yahoo to find relevant documents (entering specific keywords queries of interest in search box)
• Deep query searches i.e. fetching searchable database from eBay.com's product search engines or Business.com's service directory, etc.

To use the web as an effective resource and knowledge discovery researchers have developed efficient data mining techniques to extract relevant data easily, smoothly and cost-effectively.




Source: http://ezinearticles.com/?Basics-of-Web-Data-Mining-and-Challenges-in-Web-Data-Mining-Process&id=4937441

Data Extraction - A Guideline to Use Scrapping Tools Effectively

So many people around the world do not have much knowledge about these scrapping tools. In their views, mining means extracting resources from the earth. In these internet technology days, the new mined resource is data. There are so many data mining software tools are available in the internet to extract specific data from the web. Every company in the world has been dealing with tons of data, managing and converting this data into a useful form is a real hectic work for them. If this right information is not available at the right time a company will lose valuable time to making strategic decisions on this accurate information.

This type of situation will break opportunities in the present competitive market. However, in these situations, the data extraction and data mining tools will help you to take the strategic decisions in right time to reach your goals in this competitive business. There are so many advantages with these tools that you can store customer information in a sequential manner, you can know the operations of your competitors, and also you can figure out your company performance. And it is a critical job to every company to have this information at fingertips when they need this information.

To survive in this competitive business world, this data extraction and data mining are critical in operations of the company. There is a powerful tool called Website scraper used in online digital mining. With this toll, you can filter the data in internet and retrieves the information for specific needs. This scrapping tool is used in various fields and types are numerous. Research, surveillance, and the harvesting of direct marketing leads is just a few ways the website scraper assists professionals in the workplace.

Screen scrapping tool is another tool which useful to extract the data from the web. This is much helpful when you work on the internet to mine data to your local hard disks. It provides a graphical interface allowing you to designate Universal Resource Locator, data elements to be extracted, and scripting logic to traverse pages and work with mined data. You can use this tool as periodical intervals. By using this tool, you can download the database in internet to you spread sheets. The important one in scrapping tools is Data mining software, it will extract the large amount of information from the web, and it will compare that date into a useful format. This tool is used in various sectors of business, especially, for those who are creating leads, budget establishing seeing the competitors charges and analysis the trends in online. With this tool, the information is gathered and immediately uses for your business needs.

Another best scrapping tool is e mailing scrapping tool, this tool crawls the public email addresses from various web sites. You can easily from a large mailing list with this tool. You can use these mailing lists to promote your product through online and proposals sending an offer for related business and many more to do. With this toll, you can find the targeted customers towards your product or potential business parents. This will allows you to expand your business in the online market.

There are so many well established and esteemed organizations are providing these features free of cost as the trial offer to customers. If you want permanent services, you need to pay nominal fees. You can download these services from their valuable web sites also.

Maulik Jyotishi is the owner of scrapping expert website a company which specializes in email extractor and data extraction from web pages.




Source: http://ezinearticles.com/?Data-Extraction---A-Guideline-to-Use-Scrapping-Tools-Effectively&id=3600918

Data Management Services

In recent studies it has been revealed that any business activity has astonishing huge volumes of data, hence the ideas has to be organized well and can be easily gotten when need arises. Timely and accurate solutions are important in facilitating efficiency in any business activity. With the emerging professional outsourcing and data organizing companies nowadays many services are offered that matches the various kinds of managing the data collected and various business activities. This article looks at some of the benefits that accrue of offered by the professional data mining companies.

Entering of data

These kinds of services are quite significant since they help in converting the data that is needed in high ideal and format that is digitized. In internet some of this data can found that is original and handwritten. In printed paper documents and or text are not likely to contain electronic or needed formats. The best example in this context is books that need to be converted to e-books. In insurance companies they also depend on this process in processing the claims of insurance and at the same time apply to the law firms that offer support to analyze and process legal documents.

EDC

That is referred to as electronic data. This method is mostly used by clinical researchers and other related organization in medical. The electronic data and capture methods are used in the utilization in managing trials and research. The data mining and data management services are given in upcoming databases for studies. The ideas contained can easily be captured, other services being done and the survey taken.

Data changing

This is the process of converting data found in one format to another. Data extraction process often involves mining data from an existing system, formatting it, cleansing it and can be installed to enhance both availability and retrieving of information easily. Extensive testing and application are the requirements of this process. The service offered by data mining companies includes SGML conversion, XML conversion, CAD conversion, HTML conversion, image conversion.

Managing data service

In this service it involves the conversion of documents. It is where one character of a text may need to be converted to another. If we take an example it is easy to change image, video or audio file formats to other applications of the software that can be played or displayed. In indexing and scanning is where the services are mostly offered.

Data extraction and cleansing

Significant information and sequences from huge databases and websites extraction firms use this kind of service. The data harvested is supposed to be in a productive way and should be cleansed to increase the quality. Both manual and automated data cleansing services are offered by data mining organizations. This helps to ensure that there is accuracy, completeness and integrity of data. Also we keep in mind that data mining is never enough.

Web scraping, data extraction services, web extraction, imaging, catalog conversion, web data mining and others are the other management services offered by data mining organization. If your business organization needs such services here is one that can be of great significance that is web scraping and data mining




Source: http://ezinearticles.com/?Data-Management-Services&id=7131758

Healthcare Marketing Series - Data Mining - The 21st Century Marketing Gold Rush

There is gold in them there hills! Well there is gold right within a few blocks of your office. Mining for patients, not unlike mining for gold or drilling for oil requires either great luck or great research.

It's all about the odds.

It's true that like old Jed from the Beverly Hillbillies, you might just take a shot and strike oil. But more likely you might drill a dry hole or dig a mine and find dirt not diamonds. Without research you might be a mere 2 feet from pay dirt, but drilling or mining in just the wrong spot.

Now oil companies and gold mining companies spend millions, if not, billions of dollars studying where and how to effectively find the "mother load". If market research is good enough for the big boys, it should be good enough for the healthcare provider. Remember as a health care professional you probably don't have the extras millions laying around to squander on trial and error marketing.

If you did there would be little need for you to market to find new patients to help.

In previous articles in the Health Care Marketing Series we talked about developing a marketing strategy, using metrics to measure the performance of your marketing execution, developing effective marketing warheads based on your marketing strategy, evaluating the most efficient ways to deliver those warheads, your marketing missile systems, and tying several marketing methods together into a marketing MIRV.

If you have been following along with our articles and starting to integrate the concepts detailed in them, by now you should have an excellent marketing infrastructure. Ready to launch laser guided marketing missiles tipped with nuclear marketing MIRVs. The better you have done your research, the more detailed your marketing strategy, the more effective and efficient your delivery systems, the bigger bang you'll receive from your marketing campaign. And ultimately the more lives you will help to change of patients that truly can benefit from your skills and talents as a doctor.

Sounds like you're ready for healthcare marketing shock and awe.

Everything is ready to launch, this is great, press the button and fire away!

Ah, but wait just a minute, General. What is the target? Where are they? What are the aiming coordinates?

The target? Why of course all those sick people out there.

Where are they? Well of course, out there!

The coordinates? Man just press the button, carpet bomb man. Carpet bomb!

This scenario is designed to show you how quickly the wheels can come off even the best intended marketing war machine. It brings us back full circle. We are right back to our original article on marketing strategy.

But this time we are going to introduce the concept of data mining. If you remember, our article on marketing strategy talked about doing research. We talked about research as the true cornerstone of all marketing efforts.

What is the target, General?

Answering this question is a little difficult and the truth is each healthcare provider needs to determine his or her high value target. And more importantly needs to know how to determine his or her high value targets.

Let's go back to our launch scenario to illustrate this point. Let's continue with our military analogy. Let's say we have several aircraft carriers, a few destroyers and a fleet of rowboats, making up our marketing battlefield.

As we have discussed previously, waging a marketing war, like any war, consumes resources. So do we want to launch our nuclear marketing MIRVs, the most valuable resources in our arsenal, and target the fleet of rowboats?

Or would it be wiser to target those aircraft carriers?

Well the obvious answer is "get those carriers".

But here is where things get a little tricky. One man's aircraft carrier is another man's rowboat.

You have to data mine your practice to determine which targets are high value targets.

What goes into that data mining process? Well first and foremost, what conditions do you 1.like to treat, 2. have a proven track record of treating and 3. obtain a reasonable reimbursement for treating.

In my own practice, I typically do not like or enjoy treating shoulder problems. I don't know if I don't like treating shoulders because I haven't had great results with them or if I haven't had great results, because I don't like treating them. Needless to say my reimbursement for treating shoulder cases is relatively low.

So do I really want to carpet bomb my marketing terrain and come up with 10 new cases of rotator cuff tears? These cases, for more than one reason, are my rowboats.

On the contrary, I like to treat neurological conditions like chronic pain; Neuropathy patients, Spinal Stenosis patients, Tinnitus patients, patients with Parkinson's Disease and Multiple Sclerosis patients. I've had results with these types of cases that have been good enough to publish. Because they are complex and difficult cases, I obtain a better than average reimbursement for my efforts. These cases are my aircraft carriers. If my marketing campaign brings me ten cases with these types of problems, chances are that the patient will obtain some great relief, I will find working with them an intellectual and stimulating challenge and my marketing efforts will bring me a handsome return on investment.

So the first lesson of data mining is to identify your aircraft carriers. They must be "your" aircraft carriers. You must have a good personal track record of helping these types of patients. You should enjoy treating these types of cases. And you should be rewarded for your time and expertise.

That's the first step in the process. Identifying your high value targets. The next step is THE most important aspect of healthcare marketing. As I discussed above, I enjoy working with complex neurological cases. But how many of these types of patients exist in my marketing terrain and are they looking for the type of help I can offer?

Being able to accurately answer these important questions is the single most valuable information I can extract using data mining.

It doesn't matter if I like treating these cases. It doesn't matter if I make a good living treating these cases. It doesn't matter if my success in treating these cases has made the local news. What matters is 1. do these types of cases exist in my neighborhood and 2. are they looking for the help I can provide to them?

You absolutely positively need to know who is looking for what in your marketing terrain and if what people are clamoring for is what you have to offer.

This knowledge is the most powerful tool in your marketing arsenal. It's your secret weapon. It is the foundation of your marketing strategy. It is so important that you should consider moving your office if the results of your data mining don't reveal an ocean full of aircraft carriers in your marketing terrain for you to target.

If your market research does not reveal an abundance of aircraft carriers on your horizon, you need to either 1. move to a new battlefield, 2. re-target your efforts towards the destroyers in your market or 3. try to create a market.

Let's look at your last choice. Trying to create a market. Unless you are Coke or Pepsi, your ability to create a market as a health care provider is extremely limited. To continue on with our analogy, to create a market requires converting rowboats into, at least, destroyers, but better yet aircraft carriers.

What would it cost if you took a rowboat to a ship yard and told them to rebuild it as an aircraft carrier?

This is what you face if you try to create a market where none exists. Unless you have a personality flaw and thrive on selling ice to Eskimos, creating a market is not a rewarding proposition.

So scratch this option off the table right now.

What about re-targeting your campaign towards destroyers? That's a viable option. It's a good option. It's probably your best option. It's an option that will likely give you your best return on investment. It is recommended that you focus your arsenal on the destroyers while at the same time never passing on an opportunity to sink an aircraft carrier.

So what is the secret? How do you data mine for aircraft carriers?

Well its quite simple in the internet age. Just use the services of a market research firm. I like http://www.marketresearch.com They will do the data mining for you.

They can provide market intelligence that will tell you not only what the health care aircraft carriers are, but also where they are.

With this information, you will have a competitive advantage in your marketing battlefield. You can segment, and target high value targets in your area while your competitors squander their marketing resources on rowboats. Or even worse carpet bomb and hit ocean water, not valuable targets.

Your marketing strategy should be highly targeted. Your marketing resources should be well spent. As we discussed in our very first article on true "Marketing Strategy" you should enter the battle against your competition already knowing your have won.

What gives you this dominant position in the market, is knowing ahead-of-time, who is looking for what in your marketing terrain. In other words, not trying to create a market, but rather identifying existing market niches, specifically targeting them with laser guided precision and having headlines and ad copy based on your strength versus the weakness of your competition within that niche.

This research-based marketing strategy is sure to cause a big bang with potential patients.

And leave your competition trying to sell ice to Eskimos.

I hope you see how important market research is and why it is a good thing to spend some of your marketing budget on research before you waste your marketing resources on poorly targeted low value or no-value targets. This article was intended to give you a glimpse at how to use data mining and consumer demographics information as a foundation for the development of a scientific research-based marketing strategy. This article shows you how to use existing resources to give your marketing efforts (and you) a competitive advantage.




Source: http://ezinearticles.com/?Healthcare-Marketing-Series---Data-Mining---The--21st-Century-Marketing-Gold-Rush&id=1486283

Data Mining Software - Discover Software Modernization

Data mining software is usually an application that one uses and covers mostly with one's knowledge in the discovery of software modernization. Mining data software involves the understanding of the software artifacts that exist and the mining data tools. This process has very close relations with reverse engineering. The knowledge that one gains from studying data software that exists is usually presented in forms of models and by doing these queries one can be in a position to make his personal data mining software. With the knowledge that someone gains it must be applicable and one must also know the mining data tools that are suppose to be used apart from the soft wares. One can be able to know very widely about the mining data tools that are there in mining data software by doing computer science as a course. Computer science covers widely on what are the procedures, steps of mining data software and how can use the mining data tools.

This software is mostly used in making of databases schemes. Making of databases is not as easy as many would think it requires one to have some knowledge about computer engineering and the basic concepts of computers.;This software is mostly used in data crawling because it can be in a position to store data and one can be able to retrieve the data when needed.

The softwares are not that cheap they come in different varieties and it will depend on which information or the database on which one is coming up with.

Data mining software are usually in different levels there is the data level, design level, application level, architectural level, call graph level and program level it will depend on which level one is covering and this come together with mining data tools.

Data software's have increased rapidly through the introduction of computers and ERP definition. Computers hackers have been able to get the softwares at a very low price and this has made data mining to become very easy and quick to use in the shops and supermarkets and also government institutions. One cannot do data crawling without having the basic knowledge about data mining soft wares because soft wares are the programmes that are usually installed into the computer and without the programmes then no data can be processed.

There are a lot of challenges that come with the use of the mining soft ware. One can easily crush the software he is using or the softwares can easily break they are normally sold on CDS one can easily break it or loose it.

High chances of losing the data that someone is coming up with is very high because computers easily crash due to some difficulties that they experience or a virus can easily crush the computer.

Mining software take a very large space and in most of the computers. The reason behind this is because, data crawling use graphics. Graphics usually occupy a lot of space in terms of the size of the local disk. One is suppose to look for a computer that has very good memory. Data crawling is something that needs to be updated each and every time something appears along the way.

Victor C. has many hobbies and interests. As well being a keen blogger and article writer for many sites, he has also recently created a site focusing on data mining tools. The site is constantly being updated.



Source: http://ezinearticles.com/?Data-Mining-Software---Discover-Software-Modernization&id=5054991

Facts on Data Mining

Data mining is the process of examining a data set to extract certain patterns. Companies use this process to determine the outcome of their existing goals. They summarize this information into useful methods to create revenue and/or cut costs. When search engines are accessed, they begin to build lists of links from the first page it accesses. It continues this process throughout the site until it reaches the root page. This data not only includes text, but also numbers and facts.

Data mining focuses on consumers in relation to both "internal" (price, product positioning), and "external" (competition, demographics) factors which help determine consumer price, customer satisfaction, and corporate profits. It also provides a link between separate transactions and analytical systems. Four types of relationships are sought with data mining:

o Classes - information used to increase traffic
o Clusters - grouped to determine consumer preferences or logical relationships
o Associations - used to group products normally bought together (i.e., bacon, eggs; milk, bread)
o Patterns - used to anticipate behavior trends

This process provides numerous benefits to businesses, governments, society, and especially individuals as a whole. It starts with a cleaning process which removes errors and ensures consistency. Algorithms are then used to "mine" the data to establish patterns. With all new technology, there are positives and negatives. One negative issue that arises from the process is privacy. Although it is against the law, the selling of personal information over the Internet has occurred. Companies have to obtain certain personal information to be able to properly conduct their business. The problem is that the security systems in place are not adequately protecting this information.

From a customer viewpoint, data mining benefits businesses more than their interests. Their personal information is out there, possibly unprotected, and there is nothing they can do until a negative issue arises. On the other hand, from the business side, it helps enhance overall operations and aid in better customer satisfaction. In regards to the government, they use personal data to tighten security systems and protect the public from terrorism; however, they want to protect people's privacy rights as well. With numerous servers, databases, and websites out there, it becomes increasingly difficult to enforce stricter laws. The more information we introduce to the web, the greater the chances of someone hacking into this data.

Better security systems should be developed before data mining can truly benefit all parties involved. Privacy invasion can ruin people's lives. It can take months, even years, to regain a level of trust that our personal information will be protected. Benefits aside, the safety and well being of any human being should be top priority.




Source: http://ezinearticles.com/?Facts-on-Data-Mining&id=3640795

Data Mining and Its Impact on Business

Today, businesses are collecting more information that is available in a variety of formats. This includes: operational data, sales reports, customer data, inventory lists, forecast data, etc. In order to effectively manage and grow the business, all of the data gathered requires effective management and analysis. One such way of controlling the vast amount of information flow is a process called Data Mining.

Data mining is the process of taking a large amount of data and analyzing it from a variety of angles and putting into a format that makes it useful information to help a business improve operations, reduce costs, boost revenue, and make better business decisions. Today, effective data mining software has developed to help a business to collect and analyze useful information.

This process allows a business to collect data from a variety of sources, analyze the data using software, load the information into a database, store the information, and provide analyzed data in a useful format such as a report, table, or graph. As it relates to business analysis and business forecasting, the information analyzed is classified to determine important patterns and relationships. The idea is to identify relationships, patterns, and correlations from a broad number of different angles from a large database. These kinds of software and techniques allow a business easy access to a much simpler process which makes it more lucrative.

Data mining works allows a company to use the information to maintain competitiveness in a highly competitive business world. For instance, a company may be collecting a large volume of information from various regions of the country such as a consumer national survey. The software can compile the mined data, categorize it, and analyze it, to reveal a host of useful information that a marketer can use for marketing strategies. The outcome of the process should be an effective business analysis that allows a company to fully understand the information in order to make accurate business decisions that contributes to the success of the business. An example of a very effective use of data mining is acquiring a large amount of grocery store scanner data and analyzing it for market research. Data mining software allows for statistical analysis, data processing, and categorization, which all helps achieve accurate results.

It is mostly used by businesses with a strong emphasis on consumer information such shopping habits, financial analysis, marketing assessments...etc. It allows a business to determine key factors such as demographics, product positioning, competition, pricing, customer satisfaction, sales, and business expenditures. The result is the business is able to streamline its operations, develop effective marketing plans, and generate more sales. The overall impact is an increase in revenue and increased profitability.

For retailers, this process allows them to use of sales transactions to develop targeted marketing campaigns based on their customers shopping habits. Today, mining applications and software are available on all system sizes and platforms. For instance, the more information that has to be gathered and processed, the bigger the database. As well, the type of software a business will use depends on how complicated the data mining project. The more multifaceted the queries and the more queries performed, the more powerful system will be needed.

When a business harnesses the power of this system, they are able to gain important knowledge that will help them not only develop effective marketing strategies leading to better business decisions, but it will help identify future trends in their particular industry. Data mining has become an essential tool to help businesses gain a competitive edge.

Managing your organization well is critical - by using data mining software and being on top of performance management systems, you can ensure that your organization's information technology is up to par!



Source: http://ezinearticles.com/?Data-Mining-and-Its-Impact-on-Business&id=4528755

Data Mining Social Networks, Smart Phone Data, and Other Data Base, Yet Maintaining Privacy

Is it possible to data mine social networks in such a way to does not hurt the privacy of the individual user, and if so, can we justify doing such? It wasn't too long ago the CEO of Google stated that it was important that they were able to keep data of Google searches so they can find disease, flu, and food born medical clusters. By using this data and studying the regions in the searches to help fight against outbreaks of diseases, or food borne illnesses in the distribution system. This is one good reason to store the data, and collect it for research, as long as it is anonomized, then theoretically no one is hurt.

Unfortunately, this also scares the users, because they know if the searches are indeed stored, this data can be used against them in the future, for instance, higher insurance rates, bombardment of advertising, or get them put onto some sort of future government "thought police" watch-list. Especially considering all the political correctness, and new ways of defining hate speech, bullying, and what is, what isn't, and what might be a domestically home-grown terrorist. The future concept of the thought police is very scary to most folks.

Usually if you want to collect data from a user, you have to give them something back in return, and therefore they are willing to sign away certain privacy rights on that data in trade for the use of such services; such as on their cell phone, perhaps a free iPhone app or a virtual product in an online social network.

Artificially Intelligent Search Features

It is no surprised that AI search features are getting smarter, even able to anticipate your next search question, or what you are really trying to ask, even second guessing your question for instance. Now then, let's discuss this for a moment. Many folks very much enjoy the features of Amazon.com search features, which use artificial intelligence to recommend potential other books, which they might be interested in. And therefore the user probably does not mind giving away information about itself, for this upgraded service or ability, nor would the person mind having cookies put onto their Web browser.

Nevertheless, these types of systems are always exploited for other purposes. For instance consider the Federal Trade Commission's do not call list, and consider how many corporations, political party organizations, and all of their affiliates and partners were able to bypass these rules due to the fact that the consumer or customer had bought something from them in the last six months. This is not what consumers or customers had in mind when they decided they wanted to have this "do not call list" and the resultant and response from the market place, well, it proves we cannot trust the telecommunication companies, their lobbyists, or the insiders within their group (many of which over the years have indeed been somehow connected to the intelligence agencies - AT&T - NSA Echelon for example.)

Now then, this article is in no way to be considered a conspiracy theory, it is just a known fact, yes national security does need access to such information, and often it might be relevant, catching bad guys, terrorists, spies, etc. The NSA is to protect the American People. However, when it comes to the telecommunication companies, their job is to protect shareholder's equity, maximize quarterly profits, expand their business models, and create new profit centers in their corporations.

Thus, such user data will be and has been exploited for future profits against the wishes of the consumer, without the consumer benefiting from free services for lower prices in any way. If there is an explained reason, trade-off, and a monetary consideration, the consumer might feel obliged to have additional calls bothering them while they are at home, additional advertising, and tracking of their preferences for ease of use and suggestions. What types of suggestions?

Well, there is a Starbucks two-blocks from here, turn right, then turn left and it is 200 yards, with parking available; "Sale on Frappachinos for gold-card holders today!" In this case the telecommunication company tracks your location, knows your preferences, and collects a small fee from Starbucks, and you get a free-phone, and 20% off your monthly 4G wireless fee. Is that something a consumer might want; when asked 75% of consumers or smart phone users say; yes. See that point?

In the future smart phones may have data transferred between them, rather than going through a given or closest cell tower. In other words, packets of information may go from your cell phone, to the next nearest cell phone, to another near cell phone, to the person which is intended to receive it. And the data passing through each mobile device, will not be able to read any of the information which was it is not assigned to receive as it wasn't sent to it. By using such a scheme telecommunication companies can expand their services without building more new cell towers, and therefore they can lower the price.

However, it also means that when you lay your cell phone on the table, and it is turned on it would be constantly passing data through it, data which is not yours, and you are not getting paid for that, even though you had to purchase the smart phone. But if the phone was given to you, with a large battery, so it wouldn't go dead during all those transmissions, you probably wouldn't care, as long as your data packets of information were indeed safe and no one else could read them.

This technology exists now, and is being discussed, and consider if you will that the whole strategy of networking smart cell phones or personal tech devices together is nothing new. For instance, the same strategies have been designed for satellites, and to use an analogy, this scheme is very similar to the strategies FedEx uses when it sends packages to the next nearest FedEx office if that is their destination, without sending all of the packages all the way across the country to the central Memphis sort, and then all the way back again. They are saving time, fuel, space, and energy, and if cell phones did this it would save the telecommunication companies mega bucks in the savings of building new cell towers.

As long as you got a free cell phone, which many of us do, unless we have the mega top of the line edition, and if they gave you a long-lasting free battery it is win-win for the user. You probably wouldn't care, and the telecommunication companies could most likely lower the cost of services, and not need to upgrade their system, because they can carry a lot more data, without hundreds of billions of dollars in future investments.

Also a net centric system like this is safer to disruption in the event of an emergency, when emergency communications systems take precedence, putting every cell phone user as secondary traffic at the cell towers, which means their calls may not even get through.

Next, the last thing the telecommunication company would want to do is to data mine that data, or those packets of information from people like a soccer mom calling her son waiting at the bus stop at school. And anyone with a cell phone certainly wouldn't want their packets of information being stolen from them and rerouted because someone near them hacked into the system and had a cell phone that was displaying all of their information.

You can see the problems with all this, but you can also see the incredible economies of scale by making each and every cell phone a transmitter and receiver, which it already is in principle anyway, at least now for all data you send and receive. In the new system, if all the data which is closest by is able to transfer through it, and send that data on its way. The receiving cell phone would wait for all the packets of data were in, and then display the information.

You can see why such a system also might cause people to have a problem with it because of what they call net neutrality. If someone was downloading a movie onto their iPad using a 3G or 4G wireless network, it could tie up all the cell phones nearby that were moving the data through them. In this case, it might upset consumers, but if that traffic could be somewhat delayed by priority based on an AI algorithm decision matrix, something simple, then such a tactic for packet distribution plan might allow for this to occur without disruption from the actual cell tower, meaning everyone would be better off. Therefore we all get information flow faster, more dispersed, and therefore safer from intruders. Please consider all this.




Source: http://ezinearticles.com/?Data-Mining-Social-Networks,-Smart-Phone-Data,-and-Other-Data-Base,-Yet-Maintaining-Privacy&id=4867112

Internet Data Mining - How Does it Help Businesses?

Internet has become an indispensable medium for people to conduct different types of businesses and transactions too. This has given rise to the employment of different internet data mining tools and strategies so that they could better their main purpose of existence on the internet platform and also increase their customer base manifold.

Internet data-mining encompasses various processes of collecting and summarizing different data from various websites or webpage contents or make use of different login procedures so that they could identify various patterns. With the help of internet data-mining it becomes extremely easy to spot a potential competitor, pep up the customer support service on the website and make it more customers oriented.

There are different types of internet data_mining techniques which include content, usage and structure mining. Content mining focuses more on the subject matter that is present on a website which includes the video, audio, images and text. Usage mining focuses on a process where the servers report the aspects accessed by users through the server access logs. This data helps in creating an effective and an efficient website structure. Structure mining focuses on the nature of connection of the websites. This is effective in finding out the similarities between various websites.

Also known as web data_mining, with the aid of the tools and the techniques, one can predict the potential growth in a selective market regarding a specific product. Data gathering has never been so easy and one could make use of a variety of tools to gather data and that too in simpler methods. With the help of the data mining tools, screen scraping, web harvesting and web crawling have become very easy and requisite data can be put readily into a usable style and format. Gathering data from anywhere in the web has become as simple as saying 1-2-3. Internet data-mining tools therefore are effective predictors of the future trends that the business might take.

If you are interested to know something more on Web Data Mining and other details, you are welcome to the Screen Scraping Technology site.




Source: http://ezinearticles.com/?Internet-Data-Mining---How-Does-it-Help-Businesses?&id=3860679

Data Mining in the 21st Century: Business Intelligence Solutions Extract and Visualize

When you think of the term data mining, what comes to mind? If an image of a mine shaft and miners digging for diamonds or gold comes to mind, you're on the right track. Data mining involves digging for gems or nuggets of information buried deep within data. While the miners of yesteryear used manual labor, modern data minors use business intelligence solutions to extract and make sense of data.

As businesses have become more complex and more reliant on data, the sheer volume of data has exploded. The term "big data" is used to describe the massive amounts of data enterprises must dig through in order to find those golden nuggets. For example, imagine a large retailer with numerous sales promotions, inventory, point of sale systems, and a gift registry. Each of these systems contains useful data that could be mined to make smarter decisions. However, these systems may not be interlinked, making it more difficult to glean any meaningful insights.

Data warehouses are used to extract information from various legacy systems, transform the data into a common format, and load it into a data warehouse. This process is known as ETL (Extract, Transform, and Load). Once the information is standardized and merged, it becomes possible to work with that data.

Originally, all of this behind-the-scenes consolidation took place at predetermined intervals such as once a day, once a week, or even once a month. Intervals were often needed because the databases needed to be offline during these processes. A business running 24/7 simply couldn't afford the down time required to keep the data warehouse stocked with the freshest data. Depending on how often this process took place, the data could be old and no longer relevant. While this may have been fine in the 1980s or 1990s, it's not sufficient in today's fast-paced, interconnected world.

Real-time EFL has since been developed, allowing for continuous, non-invasive data warehousing. While most business intelligence solutions today are capable of mining, extracting, transforming, and loading data continuously without service disruptions, that's not the end of the story. In fact, data mining is just the beginning.

After mining data, what are you going to do with it? You need some form of enterprise reporting in order to make sense of the massive amounts of data coming in. In the past, enterprise reporting required extensive expertise to set up and maintain. Users were typically given a selection of pre-designed reports detailing various data points or functions. While some reports may have had some customization built in, such as user-defined date ranges, customization was limited. If a user needed a special report, it required getting someone from the IT department skilled in reporting to create or modify a report based on the user's needs. This could take weeks - and it often never happened due to the hassles and politics involved.

Fortunately, modern business intelligence solutions have taken enterprise reporting down to the user level. Intuitive controls and dashboards make creating a custom report a simple matter of drag and drop while data visualization tools make the data easy to comprehend. Best of all, these tools can be used on demand, allowing for true, real-time ad hoc enterprise reporting.




Source: http://ezinearticles.com/?Data-Mining-in-the-21st-Century:-Business-Intelligence-Solutions-Extract-and-Visualize&id=7504537

The A B C D of Data Mining Services

If you are very new to the term 'data mining', let the meaning be explained to you. It is form of back office support services that are being offered by many call centers to analyze data from numerous resources and amalgamate them for some useful task. The business establishments in the present generation need to develop a strategy that helps them to cooperate with the market trends and allow them to perform well. The process of data mining is actually the retrieval process of essential and informative data that helps an organization to analyze the business perspectives and can further generate better interests in cutting cost, developing revenue and to acquire valuable data on business services/products.

It is a powerful analytical tool that permits the user to customize a wide range of data in different formats and categories as per their necessity. The data mining process is an integral part of a business plan for companies that need to undertake a diverse research on the customer building process. These analytical skills are generally performed by skilled industrial experts who assist the firms to accelerate their growth through the critical business activities. With a vast applicability in the present time, the back office support services with the data mining process is helping the businesses in understanding and predicting valuable information. Some of them include:

    Profiles of customers
    Customer buying behavior
    Customer buying trends
    Industry analysis

For a layman it is somewhat the process of processing some statistical data or methods. These processes are implemented with some specific tools that preform the following:

    Automated model scoring
    Business templates
    Computing target columns
    Database integration
    Exporting models to other applications
    Incorporating financial information

There are some benefits of Data Mining. Few of them are as follows:

    To understand the requirements of the customers which can help in efficient planning.
    Helps in minimizing risk and improve ROI.
    Generate more business and target the relevant market.
    Risk free outsourcing experience
    Provide data access to business analysts
    A better understanding of the demand supply graph
    Improve profitability by detect unusual pattern in sales, claims, transactions
    To cut down the expenses of Direct Marketing

Data mining is generally a part of the offshore back office services and outsourced to business establishments that require diverse data base on customers and their particular approach towards any service or product. For example banks, telecommunication companies, insurance companies, etc. require huge data base to promote their new policies. If you represent a similar company that needs appropriate data mining process then it is better that you outsource back office support services from a third party and fulfill your business goals with excellent results.

Katie Cardwell works as a senior sales and marketing analyst for a multinational call center company, based in United States of America. She takes care of all the business operations and analysis the back office support services that power an organization. Her extensive knowledge and expertise on Non -voice call center services such as Data Mining Services, Back office support services, etc, have helped many business players to stand with a straight spine and thus making a foothold in the data processing industry.



Source: http://ezinearticles.com/?The-A-B-C-D-of-Data-Mining-Services&id=6503339

What Poker Data Mining Can Do for a Player

Anyone who wants to be more successful in many poker rooms online should take a look at what poker data mining can do. Poker data mining involves looking into all of the past hands in a series of poker games. This can be used to help with reviewing the ways how a player plays the game of poker. This will help to determine how well someone is working when trying to play this exciting game.

Poker data mining works in that a player will review all of the past hands that a player has gotten into. This includes taking a look at the individual hands that were involved. Every single card, bet and movement will be recorded in a hand.

All of the hands can be combined to help with figuring out the wins and losses in a game alongside all of the strategies that had been used throughout the course of a game. The analysis will be used to determine how well a player has gone in a game.

The review will be used to figure out the changes in one's winnings over the course of time. This can be used in conjunction with different types of things that are going on in a game and how the game is being played. This will be used to help figure out what is going on in a game and to see what should be done correctly and what should not be handled.

The data mining that is used is handled by a variety of different kinds of online poker sites. Many of these sites will allow its customers to buy information on various previous hands that they have gotten into. This is used by all of these places as a means of helping to figure out how well a player has done in a game.

Not all places are going to offer support for poker data mining. Some of these places will refuse to work with it due to how they might feel that poker data mining will give a player an unfair advantage over other players who are not willing to pay for it. The standards that these poker rooms will have are going to vary. It helps to review policies of different places when looking to use this service.

Poker data mining can prove to be a beneficial function for anyone to handle. Poker data mining can be smart because of how it can help to get anyone to figure out how one's hand histories are working in a poker room. It will be important to see that this is not accepted in all places though. Be sure to watch for this when playing the game of poker and looking to succeed in it.



Source: http://ezinearticles.com/?What-Poker-Data-Mining-Can-Do-for-a-Player&id=5563778

Digging Up Dollars With Data Mining - An Executive's Guide

Traditionally, organizations use data tactically - to manage operations. For a competitive edge, strong organizations use data strategically - to expand the business, to improve profitability, to reduce costs, and to market more effectively. Data mining (DM) creates information assets that an organization can leverage to achieve these strategic objectives.

In this article, we address some of the key questions executives have about data mining. These include:

    What is data mining?
    What can it do for my organization?
    How can my organization get started?

Business Definition of Data Mining

Data mining is a new component in an enterprise's decision support system (DSS) architecture. It complements and interlocks with other DSS capabilities such as query and reporting, on-line analytical processing (OLAP), data visualization, and traditional statistical analysis. These other DSS technologies are generally retrospective. They provide reports, tables, and graphs of what happened in the past. A user who knows what she's looking for can answer specific questions like: "How many new accounts were opened in the Midwest region last quarter," "Which stores had the largest change in revenues compared to the same month last year," or "Did we meet our goal of a ten-percent increase in holiday sales?"

We define data mining as "the data-driven discovery and modeling of hidden patterns in large volumes of data." Data mining differs from the retrospective technologies above because it produces models - models that capture and represent the hidden patterns in the data. With it, a user can discover patterns and build models automatically, without knowing exactly what she's looking for. The models are both descriptive and prospective. They address why things happened and what is likely to happen next. A user can pose "what-if" questions to a data-mining model that can not be queried directly from the database or warehouse. Examples include: "What is the expected lifetime value of every customer account," "Which customers are likely to open a money market account," or "Will this customer cancel our service if we introduce fees?"

The information technologies associated with DM are neural networks, genetic algorithms, fuzzy logic, and rule induction. It is outside the scope of this article to elaborate on all of these technologies. Instead, we will focus on business needs and how data mining solutions for these needs can translate into dollars.

Mapping Business Needs to Solutions and Profits

What can data mining do for your organization? In the introduction, we described several strategic opportunities for an organization to use data for advantage: business expansion, profitability, cost reduction, and sales and marketing. Let's consider these opportunities very concretely through several examples where companies successfully applied DM.

Expanding your business: Keystone Financial of Williamsport, PA, wanted to expand their customer base and attract new accounts through a LoanCheck offer. To initiate a loan, a recipient just had to go to a Keystone branch and cash the LoanCheck. Keystone introduced the $5000 LoanCheck by mailing a promotion to existing customers.

The Keystone database tracks about 300 characteristics for each customer. These characteristics include whether the person had already opened loans in the past two years, the number of active credit cards, the balance levels on those cards, and finally whether or not they responded to the $5000 LoanCheck offer. Keystone used data mining to sift through the 300 customer characteristics, find the most significant ones, and build a model of response to the LoanCheck offer. Then, they applied the model to a list of 400,000 prospects obtained from a credit bureau.

By selectively mailing to the best-rated prospects determined by the DM model, Keystone generated $1.6M in additional net income from 12,000 new customers.

Reducing costs: Empire Blue Cross/Blue Shield is New York State's largest health insurer. To compete with other healthcare companies, Empire must provide quality service and minimize costs. Attacking costs in the form of fraud and abuse is a cornerstone of Empire's strategy, and it requires considerable investigative skill as well as sophisticated information technology.

The latter includes a data mining application that profiles each physician in the Empire network based on patient claim records in their database. From the profile, the application detects subtle deviations in physician behavior relative to her/his peer group. These deviations are reported to fraud investigators as a "suspicion index." A physician who performs a high number of procedures per visit, charges 40% more per patient, or sees many patients on the weekend would be flagged immediately from the suspicion index score.

What has this DM effort returned to Empire? In the first three years, they realized fraud-and-abuse savings of $29M, $36M, and $39M respectively.

Improving sales effectiveness and profitability: Pharmaceutical sales representatives have a broad assortment of tools for promoting products to physicians. These tools include clinical literature, product samples, dinner meetings, teleconferences, golf outings, and more. Knowing which promotions will be most effective with which doctors is extremely valuable since wrong decisions can cost the company hundreds of dollars for the sales call and even more in lost revenue.

The reps for a large pharmaceutical company collectively make tens of thousands of sales calls. One drug maker linked six months of promotional activity with corresponding sales figures in a database, which they then used to build a predictive model for each doctor. The data-mining models revealed, for instance, that among six different promotional alternatives, only two had a significant impact on the prescribing behavior of physicians. Using all the knowledge embedded in the data-mining models, the promotional mix for each doctor was customized to maximize ROI.

Although this new program was rolled out just recently, early responses indicate that the drug maker will exceed the $1.4M sales increase originally projected. Given that this increase is generated with no new promotional spending, profits are expected to increase by a similar amount.

Looking back at this set of examples, we must ask, "Why was data mining necessary?" For Keystone, response to the loan offer did not exist in the new credit bureau database of 400,000 potential customers. The model predicted the response given the other available customer characteristics. For Empire, the suspicion index quantified the differences between physician practices and peer (model) behavior. Appropriate physician behavior was a multi-variable aggregate produced by data mining - once again, not available in the database. For the drug maker, the promotion and sales databases contained the historical record of activity. An automated data mining method was necessary to model each doctor and determine the best combination of promotions to increase future sales.

Getting Started

In each case presented above, data mining yielded significant benefits to the business. Some were top-line results that increased revenues or expanded the customer base. Others were bottom-line improvements resulting from cost-savings and enhanced productivity. The natural next question is, "How can my organization get started and begin to realize the competitive advantages of DM?"

In our experience, pilot projects are the most successful vehicles for introducing data mining. A pilot project is a short, well-planned effort to bring DM into an organization. Good pilot projects focus on one very specific business need, and they involve business users up front and throughout the project. The duration of a typical pilot project is one to three months, and it generally requires 4 to 10 people part-time.

The role of the executive in such pilot projects is two-pronged. At the outset, the executive participates in setting the strategic goals and objectives for the project. During the project and prior to roll out, the executive takes part by supervising the measurement and evaluation of results. Lack of executive sponsorship and failure to involve business users are two primary reasons DM initiatives stall or fall short.

In reading this article, perhaps you've developed a vision and want to proceed - to address a pressing business problem by sponsoring a data mining pilot project. Twisting the old adage, we say "just because you should doesn't mean you can." Be aware that a capability assessment needs to be an integral component of a DM pilot project. The assessment takes a critical look at data and data access, personnel and their skills, equipment, and software. Organizations typically underestimate the impact of data mining (and information technology in general) on their people, their processes, and their corporate culture. The pilot project provides a relatively high-reward, low-cost, and low-risk opportunity to quantify the potential impact of DM.

Another stumbling block for an organization is deciding to defer any data mining activity until a data warehouse is built. Our experience indicates that, oftentimes, DM could and should come first. The purpose of the data warehouse is to provide users the opportunity to study customer and market behavior both retrospectively and prospectively. A data mining pilot project can provide important insight into the fields and aggregates that need to be designed into the warehouse to make it really valuable. Further, the cost savings or revenue generation provided by DM can provide bootstrap funding for a data warehouse or related initiatives.

Recapping, in this article we addressed the key questions executives have about data mining - what it is, what the benefits are, and how to get started. Armed with this knowledge, begin with a pilot project. From there, you can continue building the data mining capability in your organization; to expand your business, improve profitability, reduce costs, and market your products more effectively.




Source: http://ezinearticles.com/?Digging-Up-Dollars-With-Data-Mining---An-Executives-Guide&id=6052872

Top Data Mining Tools

Data mining is important because it means pulling out critical information from vast amounts of data. The key is to find the right tools used for the expressed purposes of examining data from any number of viewpoints and effectively summarize it into a useful data set.

Many of the tools used to organize this data have become computer based and are typically referred to as knowledge discovery tools.

Listed below are the top data mining tools in the industry:

    Insightful Miner - This tool has the best selection of ETL functions of any data mining tool on the market. This allows the merging, appending, sorting and filtering of data.
    SQL Server 2005 Data Mining Add-ins for Office 2007 - These are great add-ins for taking advantage of SQL Server 2005 predictive analytics in Office Excel 2007 and Office Visio 2007. The add-ins Allow you to go through the entire development lifecycle within Excel 2007 by using either a spreadsheet or external data accessible through your SQL Server 2005 Analysis Services instance.
    Rapidminder - Also known as YALE is a pretty comprehensive and arguably world-leading when it comes to an open-source data mining solution. it is widely used from a large number of companies an organizations. Even though it is open-source, this tool, out of the box provides a secure environment and provides enterprise capable support and services so you will not be left out in the cold.

The list is short but ever changing in order to meet the increasing demands of companies to provide useful information from years of data.



Source: http://ezinearticles.com/?Top-Data-Mining-Tools&id=1380551

Basics of Online Web Research, Web Mining & Data Extraction Services

The evolution of the World Wide Web and Search engines has brought the abundant and ever growing pile of data and information on our finger tips. It has now become a popular and important resource for doing information research and analysis.

Today, Web research services are becoming more and more complicated. It involves various factors such as business intelligence and web interaction to deliver desired results.

Web Researchers can retrieve web data using search engines (keyword queries) or browsing specific web resources. However, these methods are not effective. Keyword search gives a large chunk of irrelevant data. Since each webpage contains several outbound links it is difficult to extract data by browsing too.

Web mining is classified into web content mining, web usage mining and web structure mining. Content mining focuses on the search and retrieval of information from web. Usage mining extract and analyzes user behavior. Structure mining deals with the structure of hyperlinks.

Web mining services can be divided into three subtasks:

Information Retrieval (IR): The purpose of this subtask is to automatically find all relevant information and filter out irrelevant ones. It uses various Search engines such as Google, Yahoo, MSN, etc and other resources to find the required information.

Generalization: The goal of this subtask is to explore users' interest using data extraction methods such as clustering and association rules. Since web data are dynamic and inaccurate, it is difficult to apply traditional data mining techniques directly on the raw data.

Data Validation (DV): It tries to uncover knowledge from the data provided by former tasks. Researcher can test various models, simulate them and finally validate given web information for consistency.



Source: http://ezinearticles.com/?Basics-of-Online-Web-Research,-Web-Mining-and-Data-Extraction-Services&id=4511101

Beneficial Data Collection Services

Internet is becoming the biggest source for information gathering. Varieties of search engines are available over the World Wide Web which helps in searching any kind of information easily and quickly. Every business needs relevant data for their decision making for which market research plays a crucial role. One of the services booming very fast is the data collection services. This data mining service helps in gathering relevant data which is hugely needed for your business or personal use.

Traditionally, data collection has been done manually which is not very feasible in case of bulk data requirement. Although people still use manual copying and pasting of data from Web pages or download a complete Web site which is shear wastage of time and effort. Instead, a more reliable and convenient method is automated data collection technique. There is a web scraping techniques that crawls through thousands of web pages for the specified topic and simultaneously incorporates this information into a database, XML file, CSV file, or other custom format for future reference. Few of the most commonly used web data extraction processes are websites which provide you information about the competitor's pricing and featured data; spider is a government portal that helps in extracting the names of citizens for an investigation; websites which have variety of downloadable images.

Aside, there is a more sophisticated method of automated data collection service. Here, you can easily scrape the web site information on daily basis automatically. This method greatly helps you in discovering the latest market trends, customer behavior and the future trends. Few of the major examples of automated data collection solutions are price monitoring information; collection of data of various financial institutions on a daily basis; verification of different reports on a constant basis and use them for taking better and progressive business decisions.

While using these service make sure you use the right procedure. Like when you are retrieving data download it in a spreadsheet so that the analysts can do the comparison and analysis properly. This will also help in getting accurate results in a faster and more refined manner.



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