Monday, 30 September 2013

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/

Sunday, 29 September 2013

Microsys A1 Website Scraper Review

The A1 scraper by Microsys is a program that is mainly used to scrape websites to extract data in large quantities for later use in webservices. The scraper works to extract text, URLs etc., using multiple Regexes and saving the output into a CSV file. This tool is can be compared with other web harvesting and web scraping services.
How it works
This scraper program works as follows:
Scan mode

    Go to the ScanWebsite tab and enter the site’s URL into the Path subtab.
    Press the ‘Start scan‘ button to cause the crawler to find text, links and other data on this website and cache them.

Important: URLs that you scrape data from have to pass filters defined in both analysis filters and output filters. The defining of those filters can be set at the Analysis filters and Output filters subtabs respectively. They must be set at the website analysis stage (mode).
Extract mode

    Go to the Scraper Options tab
    Enter the Regex(es) into the Regex input area.
    Define the name and path of the output CSV file.
    The scraper automatically finds and extracts the data according to Regex patterns.

The result will be stored in one CSV file for all the given URLs.

There is a need to mention that the set of regular expressions will be run against all the pages scraped.
Some more scraper features

Using the scraper as a website crawler also affords:

    URL filtering.
    Adjustment of the speed of crawling according to service needs rather than server load.

If  you need to extract data from a complex website, just disable Easy mode: out press the  button. A1 Scraper’s full tutorial is available here.
Conclusion

The A1 Scraper is good for mass gathering of URLs, text, etc., with multiple conditions set. However this scraping tool is designed for using only Regex expressions, which can increase the parsing process time greatly.



Source: http://extract-web-data.com/microsys-a1-website-scraper-review/

Friday, 27 September 2013

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/

Thursday, 26 September 2013

Scraping Amazon.com with Screen Scraper

Let’s look how to use Screen Scraper for scraping Amazon products having a list of asins in external database.

Screen Scraper is designed to be interoperable with all sorts of databases and web-languages. There is even a data-manager that allows one to make a connection to a database (MySQL, Amazon RDS, MS SQL, MariaDB, PostgreSQL, etc), and then the scripting in screen-scraper is agnostic to the type of database.

Let’s go through a sample scrape project you can see it at work. I don’t know how well you know Screen Scraper, but I assume you have it installed, and a MySQL database you can use. You need to:

    Make sure screen-scraper is not running as workbench or server
    Put the Amazon (Scraping Session).sss file in the “screen-scraper enterprise edition/import” directory.
    Put the mysql-connector-java-5.1.22-bin.jar file in the “screen-scraper enterprise edition/lib/ext” directory.
    Create a MySQL database for the scrape to use, and import the amazon.sql file.
    Put the amazon.db.config file in the “screen-scraper enterprise edition/input” directory and edit it to contain proper settings to connect to your database.
    Start the screen scraper workbench

Since this is a very simple scrape, you just want to run it in the workbench (most of the time you want to run scrapes in server mode). Start the workbench, and you will see the Amazon scrape in there, and you can just click the “play” button.

Note that a breakpoint comes up for each item. It would be easy to save the scraped details to a database table or file if you want. Also see in the database the “id_status” changes as each item is scraped.

When the scrape is run, it looks in the database for products marked “not scraped”, so when you want to re-run the scrapes, you need to:

UPDATE asin
SET `id_status` = 0

Have a nice scraping! ))

P.S. We thank Jason Bellows from Ekiwi, LLC for such a great tutorial.


Source: http://extract-web-data.com/scraping-amazon-com-with-screen-scraper/

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/

Tuesday, 24 September 2013

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/

Monday, 23 September 2013

Advantages of Data Mining in Various Businesses

Data mining techniques have advantages for several types of businesses, as well as there are more to be discovered over time. Since the era of the computer, things have been changing pretty quickly and every new step in the technology is equivalent to a revolution. Communication itself has not been enough. As compared to the present times, the data analyzers in the past have not achieved the chance to go further with the data they have in hand. Today, this data isn't used for selling more of a product but to foresee future risks as well as prevent them.

All are benefiting from modern these techniques even from smaller to large enterprises. They can now predict the outcome of a particular marketing campaign by analyzing them. However, in order for these techniques to be successful, the data must be arranged accurately. If your data is disseminated, you need to bring it in a meeting and then feed into the systems for the algorithms to figure it out. To put it shortly, no matter how small or big your business might be you always need to have the right system when collecting data from your customers, transactions and all business activities.

Advantages of Data Mining For Businesses

Businesses can truly benefit from its latest techniques; however, in the future, data mining techniques are expected to be even more concise and effective than they are today. Here are the essential techniques that you need to understand:

· Big companies providing the free web based email services can use data mining techniques to catch spam emails from their customer's inboxes. Their software uses a technique to assess whether an email is a spam or not. These techniques are first tested and validated before they are finally used. This is to ensure they are producing the correct results.

· Large retail stores and even shopping malls could make use of these techniques by registering and recording the transactions made by their customers. When customers are buying particular sets of product, it can give them a good understanding of placing these items in the aisle. If they want to change the order and placement of the item on weekends, it could be found out after analyzing the data on their database.

· Companies manufacturing edible or drinkable products could easily use data mining techniques to increase their sales in a particular area and launch new products based on the information they've obtained. That's why the conventional statistical analysis is rigid in scenarios wherein consumer behavior is in question. However, these techniques still manages to give you good analysis for any situations.

· In call centers, the human interaction is at its peak because people are talking with another people at all times. Customers respond differently when they talk to a female representative as opposed to talking to a male representative. The response of customers to an infomercial is different from their response to an ad in the newspaper. Data could be used for the benefit of the business and is best understood with the use of data mining techniques.

· Data mining techniques are also being used in sports today for analyzing the performances of players in the field. Any game could be analyzed with the help of these techniques; even the behaviors of players could be changed on the field through this.

In short, data mining techniques are giving the organizations, enterprises and smaller businesses the power of focusing on their most productive areas. These techniques also allow stores and companies to innovate their current selling techniques by unveiling the hidden trends of their customer's behavior, background, price of the products, placement, closeness to the related products and many more.




Source: http://ezinearticles.com/?Advantages-of-Data-Mining-in-Various-Businesses&id=7568546

Sunday, 22 September 2013

Why Outsource Data Entry Services?

All large business and organizations are faced with the task of processing huge amounts of data on a daily basis. The data to be processed may range from indexing of vouchers and documents to collecting of information from customers and vendors. In order to save on the huge amount of time, energy and monetary resources which go into data entry, businesses world wide have discovered the multiple benefits of outsourcing their Data Entry Services to India. Along with quick turn around time, reliability of data accuracy and confidentiality of all client databases, outsourcing Data Entry Services to India also proves to be extremely cost-effective.

What are the kinds of Services that can be outsourced?

Most outsourcing companies provide custom made Data-Entry Services depending on the client's specifications. A few of them provided by Indian Outsourcing Companies are;

- Data entry from product catalogs to web based systems
- Entry from hard/soft copy to any preferred database format
- Insurance claims processing
- Image Entry
- Data mining and warehousing
- Data cleansing
- Entry from hospital records, patient notes and accident reports
- From e-book and e-magazine publications on the Internet
- Entry for mailing lists
- PDF document indexing
- Online data capture services
- Online order entry and follow up services
- Creating new databases and updating of existing databases for banks, airlines, government agencies
- direct marketing services and service providers
- Web based indexed document retrieval services, tools and support
- Entry of legal documents
- Indexing of vouchers and documents
- Hand written ballot/cards entry
- Online completion of surveys and responses of customers for various companies
- Business card indexing
- Custom data export/import interfaces with audits
- Bonded mail handling cash, credit and check processing
- Entry of Questionnaires
- Entry of Company Reports
- From Printed / Handwritten Source
- From Yellow Pages / White Pages
- Entry of Dictionaries, Manuals and Encyclopedia
- Entry of Surveys

What is the process?

Since most Indian companies hire only competent and highly qualified staff, outsourcing Data Entry Services to India ensures that the client is fully satisfied with the end result. Added to this the client's data confidentiality and security is viewed as extremely important. Each project goes through a specific data entry service plan that aims to fulfill the exact need of the customer and the error rate is always kept below 2-3%. The process is as follows:

- Data is processed, scanned and uploaded on to secure FTP online server
- Data is subsequently accessed over VPN and downloaded
- Data is individually indexed and sorted into private work folders
- Data is entered into specific applications as per client's requirements
- Data is checked and assessed for errors
- Data is finally sent to the customers

What are the benefits of outsourcing Services?

Oversees companies outsourcing their Data Entry Services to India have the assurance that their projects will be delivered on time with the highest levels of data quality and accuracy. The cost competitive prices, highly qualified employees, fast turnaround time and data security offered by outsourcing vendors, make sure that all of the client's objectives and goals are met. Outsourcing of these Services to India has been proven to be an advantageous choice for businesses worldwide.

Outsource2india provides Outsourcing Services and Solutions, Data Entry Services data processing services, data management, Business and Knowledge Process Outsourcing, Call Center Services, Healthcare Services, Engineering Services, Software Services, Digital Image Editing Services, Research & Analysis Services, Creative Services, Web Analytics Services, etc.




Source: http://ezinearticles.com/?Why-Outsource-Data-Entry-Services?&id=1428867

Thursday, 19 September 2013

RFM - A Precursor to Data Mining

RFM in Action

RFM was initially utilized by marketers in the B-2-C space - specifically in industries like Cataloging, Insurance, Retail Banking, Telecommunications and others. There are a number of scoring approaches that can be used with RFM. We'll take a look at three:

RFM - Basic Ranking
RFM - Within Parent Cell Ranking
RFM - Weighted Cell Ranking

Each approach has experienced proponents that argue one over the other. The point is to start somewhere and experiment to find the one that works best for your company and your customer base. Let's look at a few examples.

RFM - Basic Ranking

This approach involves scoring customers based on each RFM factor separately. It begins with sorting your customers based on Recency, i.e., the number of days or months since their last purchase. Once sorted in ascending order (most recent purchasers at the top), the customers are then split into quintiles, or five equal groups. The customers in the top quintile represent the 20% of your customers that most recently purchased from you.

This process is then undertaken for Frequency and Monetary as well. Each customer is in one of the five cells for R, F, and M

Experience tells us that the best prospects for an upcoming campaign are those customers that are in Quintile 5 for each factor - those customers that have purchased most recently, most frequently and have spent the most money. In fact, a common approach to creating an aggregated score is to concatenate the individual RFM scores together resulting in 125 cells (5x5x5).

A customer's score can range from 555 being the highest, to 111 being the lowest.

RFM - Within Parent Cell Ranking

This approach is advocated by Arthur Middleton Hughes - one of the biggest proponents of RFM analysis. It begins like the one above, i.e., all customer are initially grouped into 5 cells based on Recency. The next step takes customers in a given Recency cell - say cell number 5, and then ranks those customers based on Frequency. Then customers in the 55 (RF) cell are ranked by monetary value.

RFM - Weighted Ranking

Weightings used by RFM practitioners vary. For example some advocate adding the RFM score together - thus giving equal weight to each factor. Consequently, scores can range from 15 (5+5+5) to 3 (1+1+1). Another weighting arrangement often used is, 3xR + 2xF + 1xM. In this case, scores can range from 30 to 3.

So which to use? In reality, there are many other permutations of approaches that are being used today. Best-practice marketing analytics requires a fine mix of mathematical and statistical science, creativity and experimentation. Bottom line, test multiple scoring methods to see which works best for your unique customer base.

Establishing a Score Threshold

After a test or production campaign, you will find that some of the cells were profitable while some were not. Let's turn to a case study to see how you can establish a threshold that will help maximize your profitability. This study comes from Professor Charlotte Mason of the Kenan-Flagler Business School and utilizes a real-life marketing study performed by The BookBinders Book Club (Source:Recency, Frequency and Monetary (RFM) Analysis, Professor Charlotte Mason, Kenan-Flagler Business School, University of North Carolina, 2003).

BookBinders is a specialty book seller that utilizes multiple marketing channels. BookBinders traditionally did mass marketing and wanted to test the power of RFM. To do so, they initially did a random mailing to 50,000 customers. The customers were mailed an offer to purchase The Art History of Florence. Response data was captured and a "post-RFM" analysis was completed. This "post analysis" was done by freezing the files of the 50,000 test customers prior to the actual test offer. Thus, the impact of this test campaign did not effect the analysis by coding many (the actual buyers) of the 50,000 test subjects as the most recent purchasers. The results firmly support the use of RFM as a highly effective segmentation approach.

Purchased the book = yes; months since last purchase = 8.61; total # purchases = 5.22; dollars spent = 234.30
Purchased the book = no; Months since last purchase = 12.73; total # purchases = 3.76; dollars spent = 205.74

Customers that purchased the book were more recent purchasers, more frequent purchasers and had spent the most with BookBinders.

The response rate for the top decile (18%) was twice the response rate associated with the 5th decile (9%).

Results from this test were then used by BookBinders to identify which of their remaining customers should receive the same mailing. BookBinders used a breakeven response rate calculation to determine the appropriate RFM cells to mail.

The following cost information was used as input:

Cost per Mail-piece $0.50

Selling Price $18.00

BookBinders Book Cost $9.00

Shipping Costs $3.00

Breakeven is achieved when the cost of the mailing is equal to the net profit from a sale. In this case:

Breakeven = (cost to mail the offer/net profit from a single sale)

= $0.50/($18-9-3)

= ($0.50/6)

= 8.3% = Breakeven Response rate

So, according to the test offer, profit can be obtained by mailing to cells that exhibited a response rate of greater than 8.3%

RFM dramatically improved profitability by capturing 71% of buyers (3,214/4,522) while mailing only 46% of their customers (22,731/50,000). And the return on marketing expenditures using RFM was more than eight times (69.7/8.5) that of a mass mailing.

Number of Cells and Cell Size Considerations

As previously mentioned, RFM was initially utilized by companies that operated in the B-to-C marketplace and generally possessed a very large number of customers. The idea of generating 125 cells using quintiles for R, F and M has been a very good practice as an initial modeling effort. But what if you are a B-to-B marketer with relatively fewer customers? Or, what if you are a B-to-C marketer with an extremely large file with millions of customers? The answer is to use the same approach that is used in data mining -- be flexible and experiment.

Establishing a minimum test cell size is a good place to start. Arthur Hughes recommends the following formula:

Test Cell Size = 4 / Breakeven Response Rate.

The Breakeven Response Rate was addressed above in the BookBinders case study. The number "4" is a number that Hughes has found works successfully based on many studies he has performed. BookBinders Breakeven Response Rate was 8.3%. Using the above formula, you would need a minimum of 48 customers in each cell (4/0.083). BookBinders actually had 400 customers per cell, so they had more than adequate comfort in the significance of their test. In reality, BookBinders could have created as many as 1,041 cells if they were comfortable using the minimum of 48 per cell. As an example, they could have used deciles as opposed to quintiles and established 1,000 cells (10 x 10 x 10). The more cells the finer the analysis, but of course the law of diminishing returns will arise.

Other weighting considerations can be used for small files. If your Breakeven Response Rate is 3%, your minimum cell size would be 133 customers (4/0.03). Therefore, if you have 12,000 customers you could have about 90 cells (12,000/133). As such, a 5 x 5 x 4 (100 cells) or a 5 x 4 x 4 (80 cells) approach may be appropriate.

Conclusions

RFM, BI and data mining are all part of an evolutionary path that is common to many marketing organizations. While RFM has been practiced for over 40 years, it still holds great value for many organizations. Its merits include:

- Simplicity - easy to understand and implement

- Relatively low cost

- Proven ROI

- The demand on data requirements are relatively low in terms of variables required and the number of records

- Once utilized, it sets up a broader foundation (from an infrastructure and business case perspective) to undertake more sophisticated data mining efforts

RFM's challenges include:

- Contact fatigue can be a problem for the higher scoring customers. A high level cross-campaign communication strategy can help prevent this.

- Your lowest scoring customers may never hear from you. Again, a cross-campaign communications plan should ensure that all of your customers are communicated with periodically to ensure low scoring customers are given the opportunity to meet their potential. Also, data mining and the prediction of customer lifetime value can help address this shortcoming.

- RFM includes only three variables. Data mining typically finds RFM-based variables to be quite important in response models. But there are additional variables that data mining typically use (e.g., detailed transaction, demographic and firmographic) that help produce improved results. Moreover, data mining techniques can also increase response rates via the development of richer segment/cell profiles that can be used to vary offer content and incentives.

As stated before, successful marketing efforts require analytics and experimentation. RFM has proven itself as an effective approach to predicting response and improving profitability. It can be an important stage in your company's evolution in marketing analytics.




Source: http://ezinearticles.com/?RFM---A-Precursor-to-Data-Mining&id=1962283

Wednesday, 18 September 2013

What You Should Know About Data Entry at Home Portals

This is a very, very popular topic on the Internet. Companies always have reports, receipts and other sorts of data which needs processing. In the old days this would have been worked on in-house.

But thousands of companies are now learning that the Net has brought into the open a world of opportunity when they want their data entry work executed. Those who have not woken up to the outsourcing experience which is coming about globally before our very eyes will have to get with the program soon otherwise they will be left for dead.

With ever more people hooking up to the net in developing nations such as India, Pakistan and many other Eastern countries along with the continued development of outsourcing web sites such as Get A Freelancer the competition for these data entry jobs can be intense.

But we see real hopelessness out there. Some people are so desperate to get this type of work that they will be brainwashed into believing that there are millions to be had doing data entry gigs on the Net. Where ever one sees desperation you'll find the sharks lingering to sink their razor sharp ivories into their poor unsuspecting prey.

Scammers are everywhere in this work at home category and while there is proper data entry work to be found on the web there are equally those scum who would steal from their own grandmother, laying in wait for the next newbie.

Thankfully there is a web destination which cuts through the flotsam and jetsam bringing the work at home freelancer a truly splendid resource for uncovering work on the net. Data Entry At Home sends a job by email every single day. You can also find decent reviews, sometimes with videos, of data entry web sites and other work from home destinations.

A top example of a video review is the one of the Home Job Stop work at home job portal. Well worth a gander.

Riley was commissioned to produce this write up by the Virtual Server organisation who have more information on the data entry at home phenomenon. If you need articles written or SEO done for your site do contact Riley.





Source: http://ezinearticles.com/?What-You-Should-Know-About-Data-Entry-at-Home-Portals&id=1743664

Tuesday, 17 September 2013

Accelerating Accumulated Data Mining

We all have heard of Data Mining and we have all seen the abilities it can produce, but we also know how tedious the collection of data can be. It is the same for a little small company with a few customers as it is for a large company with millions of customers. Additionally how do you keep your data safe?

We have all heard of Identity Theft and the importance of secure data. But just because we have spent millions of dollars in IT work does not mean we know it is accurate? Things change fast you see; people get new telephone numbers, change addresses and jobs at least one of the three every three years. The chances of any database having accurate information is simply not possible.

Thus if we are data mining we need a way to verify which data sets are accurate and believe it or not the last set of data may not be the most accurate therefore we cannot simply discard the old data for the new data you see? We need ways to accelerate the accumulated data so we can run through it as fast as possible yet we must insure that our data mining techniques are taking into consideration miss matched data and incorrect data, along with inaccurate data.

Data Mining may have been over hyped a little and those business systems or even government data mining systems at the NSA; if they do not take into consideration these thoughts they are basically worthless and should not be considered you see? Think on this in 2006.

"Lance Winslow" - Online Think Tank forum board. If you have innovative thoughts and unique perspectives, come think with Lance; www.WorldThinkTank.net/. Lance is an online writer in retirement.





Source: http://ezinearticles.com/?Accelerating-Accumulated-Data-Mining&id=202738

Monday, 16 September 2013

Data Recovery Service

Data recovery service is a very common line of work nowadays as the use of electronic data storage media increases. Nearly every electronic gadget has some sort of memory that gets written to and therefore could become damaged or corrupt.

As data storage use increases, you can imagine that the data recovery service business niche would boom. Services are currently offered on nearly every data storage type you can imagine; examples of this are;

Hard drives, RAID, laptop, tape, flash drive, DVD, CD, Zip or Jazz drives.

It seems that you can't back stuff up enough! You could have your Home PC backed up to your laptop which in turn is backed up to the best external hard drive you could find. They are all plugged in at home, one power cut could in theory corrupt all three copies! This is unlikely, but still a possibility.

You should be able to find a data recovery service that will examine your damaged data and determine whether or not it is recoverable - Diagnose. This part should be free.

The next part should be to evaluate the best method for recovering the data, whether it is a straight forward mirror of the original data, whether they can use data recovery software to extract it or whether they have to go a bit deeper and look into editing the hexadecimal code.

The most important part is to actually recover data itself and store it on some new media such as a CD and present it to the customer at which point you will have to pay up.

The data recovery service should be able to interrogate your media without making any warranty void. You should also be able to find a service that will not charge a penny if they cannot recover your data.

By making your warranty void, I am talking about the little sticker that is neatly placed on the case of your PC or on the case of the hard disk itself or in some instances, both! If the device needs to be opened up, this will in turn damage the sticker and make your warranty void. This will stop you being able to get any money back from the manufacturer or shop for the device actually being faulty. A good, experienced company should be able to do all the work they need to do without making a warranty void in most cases.

There are hundreds of data service companies out there that can do all the things listed above - they are expensive and I can only see prices going up as demand increases.




Source: http://ezinearticles.com/?Data-Recovery-Service&id=6255314

Sunday, 15 September 2013

Data Mining - Critical for Businesses to Tap the Unexplored Market

Knowledge discovery in databases (KDD) is an emerging field and is increasingly gaining importance in today's business. The knowledge discovery process, however, is vast, involving understanding of the business and its requirements, data selection, processing, mining and evaluation or interpretation; it does not have any pre-defined set of rules to go about solving a problem. Among the other stages, the data mining process holds high importance as the task involves identification of new patterns that have not been detected earlier from the dataset. This is relatively a broad concept involving web mining, text mining, online mining etc.

What Data Mining is and what it is not?

The data mining is the process of extracting information, which has been collected, analyzed and prepared, from the dataset and identifying new patterns from that information. At this juncture, it is also important to understand what it is not. The concept is often misunderstood for knowledge gathering, processing, analysis and interpretation/ inference derivation. While these processes are absolutely not data mining, they are very much necessary for its successful implementation.

The 'First-mover Advantage'

One of the major goals of the data mining process is to identify an unknown or rather unexplored segment that had always existed in the business or industry, but was overlooked. The process, when done meticulously using appropriate techniques, could even make way for niche segments providing companies the first-mover advantage. In any industry, the first-mover would bag the maximum benefits and exploit resources besides setting standards for other players to follow. The whole process is thus considered to be a worthy approach to identify unknown segments.

The online knowledge collection and research is the concept involving many complications and, therefore, outsourcing the data mining services often proves viable for large companies that cannot devote time for the task. Outsourcing the web mining services or text mining services would save an organization's productive time which would otherwise be spent in researching.

The data mining algorithms and challenges

Every data mining task follows certain algorithms using statistical methods, cluster analysis or decision tree techniques. However, there is no single universally accepted technique that can be adopted for all. Rather, the process completely depends on the nature of the business, industry and its requirements. Thus, appropriate methods have to be chosen depending upon the business operations.

The whole process is a subset of knowledge discovery process and as such involves different challenges. Analysis and preparation of dataset is very crucial as the well-researched material could assist in extracting only the relevant yet unidentified information useful for the business. Hence, the analysis of the gathered material and preparation of dataset, which also considers industrial standards during the process, would consume more time and labor. Investment is another major challenge in the process as it involves huge cost on deploying professionals with adequate domain knowledge plus knowledge on statistical and technological aspects.

The importance of maintaining a comprehensive database prompted the need for data mining which, in turn, paved way for niche concepts. Though the concept has been present for years now, companies faced with ever growing competition have realized its importance only in the recent years. Besides being relevant, the dataset from where the information is actually extracted also has to be sufficient enough so as to pull out and identify a new dimension. Yet, a standardized approach would result in better understanding and implementation of the newly identified patterns.




Source: http://ezinearticles.com/?Data-Mining---Critical-for-Businesses-to-Tap-the-Unexplored-Market&id=6745886

Friday, 13 September 2013

Benefits of Predictive Analytics and Data Mining Services

Predictive Analytics is the process of dealing with variety of data and apply various mathematical formulas to discover the best decision for a given situation. Predictive analytics gives your company a competitive edge and can be used to improve ROI substantially. It is the decision science that removes guesswork out of the decision-making process and applies proven scientific guidelines to find right solution in the shortest time possible.

Predictive analytics can be helpful in answering questions like:

    Who are most likely to respond to your offer?
    Who are most likely to ignore?
    Who are most likely to discontinue your service?
    How much a consumer will spend on your product?
    Which transaction is a fraud?
    Which insurance claim is a fraudulent?
    What resource should I dedicate at a given time?

Benefits of Data mining include:

    Better understanding of customer behavior propels better decision
    Profitable customers can be spotted fast and served accordingly
    Generate more business by reaching hidden markets
    Target your Marketing message more effectively
    Helps in minimizing risk and improves ROI.
    Improve profitability by detecting abnormal patterns in sales, claims, transactions etc
    Improved customer service and confidence
    Significant reduction in Direct Marketing expenses

Basic steps of Predictive Analytics are as follows:

    Spot the business problem or goal
    Explore various data sources such as transaction history, user demography, catalog details, etc)
    Extract different data patterns from the above data
    Build a sample model based on data & problem
    Classify data, find valuable factors, generate new variables
    Construct a Predictive model using sample
    Validate and Deploy this Model

Standard techniques used for it are:

    Decision Tree
    Multi-purpose Scaling
    Linear Regressions
    Logistic Regressions
    Factor Analytics
    Genetic Algorithms
    Cluster Analytics
    Product Association





Source: http://ezinearticles.com/?Benefits-of-Predictive-Analytics-and-Data-Mining-Services&id=4766989

What is Data Mining?

Data mining is the process in which there is analysis of data forming different angles and perspectives and summarizing the same data into the relevant information. This kind of information could be utilized to increase the revenue, cutting the costs or both.

Software is mainly used for analyzing data and also assists in accumulation of data for the different sources and categorize and summarize the given data into some useful form.

Though the data mining is new term, the software used for mining the data was previously used. With the constant upgradations of the software and the processing power, the market tools, data mining software has increased in its accuracy. Formerly, this data mining was widely used by the businessmen for the market research and the analysis. There were few companies that used the computers to examine through the column of the supermarket data.

The data mining is the technique of running the data through the sophisticated algorithms for discovering the meaningful correlations and patterns that would have otherwise remained hidden. It is very helpful, since it aids in understanding the techniques and methods of business and you can accordingly apply your own intelligence fitting in the current market trend. Even the future performances get enhanced by the predictive analysis.

Business Intelligence operations occur in the background. Users of the mining operation can just see the end result. The users are in apposition to get the results through the mails and can also go through the recommendation through web pages and emails.

The data mining process indicates the invention of trends and tactics. The moment you discover and understand the market trends, you have the knowledge of which article is sold more and which article is sold with the other one. This kind of tend has an enormous impact on business organization. In this manner, the business gets enhanced as the market gets analyzed in a perfect manner. Due to these correlations, the performance of business organization increases to a lot of extent.

Mining gives a chance or opportunity to enhance the future performance of the business organization. There is a common philosophical phrase that, 'he who does not learn from the history is destined to repeat the same'. Therefore, if these predictions are done with the help and assistance of the historical information (data), then you can get sufficient data for improvising the products of the business organization.

Mining enables the embedding of the recommendations in the applications. Simple summary statements and the proposals can be displayed within the operational applications. Data mining also needs powerful machines. The algorithms might be applied to a Java or a Dataset code for using the same. Data mining is very useful for knowing the trends and making future predictions based on the predictive analysis. It also helps in cost cutting and increase in the revenue of the business organization

This article is part of Expertstown. You can visit Experts Town's Business Intelligence Blog for more information.




Source: http://ezinearticles.com/?What-is-Data-Mining?&id=3816784

Wednesday, 11 September 2013

Data Mining - Techniques and Process of Data Mining

Data mining as the name suggest is extracting informative data from a huge source of information. It is like segregating a drop from the ocean. Here a drop is the most important information essential for your business, and the ocean is the huge database built up by you.

Recognized in Business

Businesses have become too creative, by coming up with new patterns and trends and of behavior through data mining techniques or automated statistical analysis. Once the desired information is found from the huge database it could be used for various applications. If you want to get involved into other functions of your business you should take help of professional data mining services available in the industry

Data Collection

Data collection is the first step required towards a constructive data-mining program. Almost all businesses require collecting data. It is the process of finding important data essential for your business, filtering and preparing it for a data mining outsourcing process. For those who are already have experience to track customer data in a database management system, have probably achieved their destination.

Algorithm selection

You may select one or more data mining algorithms to resolve your problem. You already have database. You may experiment using several techniques. Your selection of algorithm depends upon the problem that you are want to resolve, the data collected, as well as the tools you possess.

Regression Technique

The most well-know and the oldest statistical technique utilized for data mining is regression. Using a numerical dataset, it then further develops a mathematical formula applicable to the data. Here taking your new data use it into existing mathematical formula developed by you and you will get a prediction of future behavior. Now knowing the use is not enough. You will have to learn about its limitations associated with it. This technique works best with continuous quantitative data as age, speed or weight. While working on categorical data as gender, name or color, where order is not significant it better to use another suitable technique.

Classification Technique

There is another technique, called classification analysis technique which is suitable for both, categorical data as well as a mix of categorical and numeric data. Compared to regression technique, classification technique can process a broader range of data, and therefore is popular. Here one can easily interpret output. Here you will get a decision tree requiring a series of binary decisions.




Source: http://ezinearticles.com/?Data-Mining---Techniques-and-Process-of-Data-Mining&id=5302867

Monday, 9 September 2013

What is Data Mining? Why Data Mining is Important?

Searching, Collecting, Filtering and Analyzing of data define as data mining. The large amount of information can be retrieved from wide range of form such as different data relationships, patterns or any significant statistical co-relations. Today the advent of computers, large databases and the internet is make easier way to collect millions, billions and even trillions of pieces of data that can be systematically analyzed to help look for relationships and to seek solutions to difficult problems.

The government, private company, large organization and all businesses are looking for large volume of information collection for research and business development. These all collected data can be stored by them to future use. Such kind of information is most important whenever it is require. It will take very much time for searching and find require information from the internet or any other resources.

Here is an overview of data mining services inclusion:

* Market research, product research, survey and analysis
* Collection information about investors, funds and investments
* Forums, blogs and other resources for customer views/opinions
* Scanning large volumes of data
* Information extraction
* Pre-processing of data from the data warehouse
* Meta data extraction
* Web data online mining services
* data online mining research
* Online newspaper and news sources information research
* Excel sheet presentation of data collected from online sources
* Competitor analysis
* data mining books
* Information interpretation
* Updating collected data

After applying the process of data mining, you can easily information extract from filtered information and processing the refining the information. This data process is mainly divided into 3 sections; pre-processing, mining and validation. In short, data online mining is a process of converting data into authentic information.

The most important is that it takes much time to find important information from the data. If you want to grow your business rapidly, you must take quick and accurate decisions to grab timely available opportunities.

Outsourcing Web Research is one of the best data mining outsourcing organizations having more than 17 years of experience in the market research industry. To know more information about our company please contact us.



Source: http://ezinearticles.com/?What-is-Data-Mining?-Why-Data-Mining-is-Important?&id=3613677

Sunday, 8 September 2013

The Need for Specialised Data Mining Techniques for Web 2.0

Web 2.0 is not exactly a new version of the Web, but rather a way to describe a new generation of interactive websites centred on the user. These are websites that offer

interactive information sharing, as well as collaboration - a case in point being wikis and blogs - and is now expanding to other areas as well. These new sites are the result of new technologies and new ideas and are on the cutting edge of Web development. Due to their novelty, they create a rather interesting challenge for data mining.

Data mining is simply a process of finding patterns in masses of data. There is such a vast plethora of information out there on the Web that it is necessary to use data mining tools to make sense of it. Traditional data mining techniques are not very effective when used on these new Web 2.0 sites because the user interface is so varied. Since Web 2.0 sites are created largely by user-supplied content, there is even more data to mine for valuable information. Having said that, the additional freedom in the format ensures that it is much more difficult to sift through the content to find what is usable.The data available is very valuable, so where there is a new platform, there must be new techniques developed for mining the data. The trick is that the data mining methods must themselves be flexible as the sites they are targeting are flexible. In the initial days of the World Wide Web, which was referred to as Web 1.0, data mining programs knew where to look for the desired information. Web 2.0 sites lack structure, meaning there is no single spot for the mining program to target. It must be able to scan and sift through all of the user-generated content to find what is needed. The upside is that there is a lot more data out there, which means more and more accurate results if the data can be properly utilized. The downside is that with all that data, if the selection criteria are not specific enough, the results will be meaningless. Too much of a good thing is definitely a bad thing. Wikis and blogs have been around long enough now that enough research has been carried out to understand them better. This research can now be used, in turn, to devise the best possible data mining methods. New algorithms are being developed that will allow data mining applications to analyse this data and return useful. Another problem is that there are many cul-de-sacs on the internet now, where groups of people share information freely, but only behind walls/barriers that keep it away from the genera results.

The main challenge in developing these algorithms does not lie with finding the data, because there is too much of it. The challenge is filtering out irrelevant data to get to the meaningful one. At this point none of the techniques are perfected. This makes Web 2.0 data mining an exciting and frustrating field, and yet another challenge in the never ending series of technological hurdles that have stemmed from the internet. There are numerous problems to overcome. One is the inability to rely on keywords, which used to be the best method to search. This does not allow for an understanding of context or sentiment associated with the keywords which can drastically vary the meaning of the keyword population. Social networking sites are a good example of this, where you can share information with everyone you know, but it is more difficult for that information to proliferate outside of those circles. This is good in terms of protecting privacy, but it does not add to the collective knowledge base and it can lead to a skewed understanding of public sentiment based on what social structures you have entry into. Attempts to use artificial intelligence have been less than successful because it is not adequately focused in its methodology. Data mining depends on the collection of data and sorting the results to create reports on the individual metrics that are the focus of interest. The size of the data sets are simply too large for traditional computational techniques to be able to tackle them. That is why a new answer needs to be found. Data mining is an important necessity for managing the backhaul of the internet. As Web 2.0 grows exponentially, it is increasingly hard to keep track of everything that is out there and summarize and synthesize it in a useful way. Data mining is necessary for companies to be able to really understand what customers like and want so that they can create products to meet these needs. In the increasingly aggressive global market, companies also need the reports resulting from data mining to remain competitive. If they are unable to keep track of the market and stay abreast of popular trends, they will not survive. The solution has to come from open source with options to scale databases depending on needs. There are companies that are now working on these ideas and are sharing the results with others to further improve them. So, just as open source and collective information sharing of Web 2.0 created these new data mining challenges, it will be the collective effort that solves the problems as well.

It is important to view this as a process of constant improvement, not one where an answer will be absolute for all time. Since its advent, the internet has changed quite significantly as well as the way users interact with it. Data mining will always be a critical part of corporate internet usage and its methods will continue to evolve just as the Web and its content does.

There is a huge incentive for creating better data mining solutions to tackle the complexities of Web 2.0. For this reason, several companies exist just for the purpose of analysing and creating solutions to the data mining problem. They find eager buyers for their applications in companies which are desperate for information on markets and potential customers. The companies in question do not simply want more data, they want better data. This requires a system that can classify and group data, and then make sense of the results.While the data mining process is expensive to start with, it is well worth for a retail company because it provides insight into the market and thus enables quick decisions.The speed at which a company which has insightful information on the marketplace can react to changes, gives it a huge advantage over the competition. Not only can the company react quickly, it is likely to steer itself in the right direction if its information is based on updated data.Advanced data mining will allow companies not only to make snap decisions, but also to plan long range strategies, based on the direction the marketplace is heading. Data mining brings the company closer to its customers. The real winners here, are the companies that have now discovered that they can make a living by improving the existing data mining techniques. They have filled a niche that was only created recently, which no one could have foreseen and have done quite a, good job at it.



Source: http://ezinearticles.com/?The-Need-for-Specialised-Data-Mining-Techniques-for-Web-2.0&id=7412130

Friday, 6 September 2013

Advantageous Data Entry Services in Era of Globalization

Data generally represent the information and can be defined with numbers or alphabetical symbols. Data entry can be determined as process that converts data from one form to another one. Such solutions usually includes almost all business fields and professional services, such as data conversion, offline data entry work, data processing, image processing, data entry outsourcing, data mining etc. One has to collect data on various topics and have to represent them in some meaningful manner.

There are several tasks for data entry services. It may includes data-entry into websites, tracking debit or credit card transactions, entry into electronic books, image formatting, keeping hard copy of office applications for scanning or printing, database for mails, use of data entry software as well as management of all these activities. In addition some time consuming tasks such as entering data in offline mode to track websites, gathering effective websites, which may need for consultation and to fill online forms. One of the good examples of data entry tasks is writing the image. You have to enter the images to incorporate pictures and attachments in magazines, e Books and white papers. Scanned images also needed to enter the details on the file. Another example of data-entry work is insurance claim. Insurance firms file a claim for insurance in process to get the cost of services. All systems for payment, form processing and insurance claims are followed by data entry services.

Data processing is also very useful tasks needed to be managed, regardless of company size or complexity. You have to follow some methods in order to accomplish your data processing tasks accurately. Such services help firms in terms of clear analysis of activities, policies, strategies and actions. Data processing and other services like data cleaning, image processing, OCR clean up, survey processing are related to provide a well-processed and complete data which can be used to get simple explanation of data.

There are plenty of advantages such services. For example data conversion is process which is very significant for any firm to drive their business powerfully. Data conversion can be considered as transfer of data from one format to another. There are also some other useful services like data transformation and many other which directly or indirectly essential for smooth functionality of any business.

Be advantageous in this competitive environment by choosing the right business services for benefits of yours and your organization.




Source: http://ezinearticles.com/?Advantageous-Data-Entry-Services-in-Era-of-Globalization&id=3134132

Wednesday, 4 September 2013

Data Mining Questions? Some Back-Of-The-Envelope Answers

Data mining, the discovery and modeling of hidden patterns in large volumes of data, is becoming a mainstream technology. And yet, for many, the prospect of initiating a data mining (DM) project remains daunting. Chief among the concerns of those considering DM is, "How do I know if data mining is right for my organization?"

A meaningful response to this concern hinges on three underlying questions:

    Economics - Do you have a pressing business/economic need, a "pain" that needs to be addressed immediately?
    Data - Do you have, or can you acquire, sufficient data that are relevant to the business need?
    Performance - Do you need a DM solution to produce a moderate gain in business performance compared to current practice?

By the time you finish reading this article, you will be able to answer these questions for yourself on the back of an envelope. If all answers are yes, data mining is a good fit for your business need. Any no answers indicate areas to focus on before proceeding with DM.

In the following sections, we'll consider each of the above questions in the context of a sales and marketing case study. Since DM applies to a wide spectrum of industries, we will also generalize each of the solution principles.

To begin, suppose that Donna is the VP of Marketing for a trade organization. She is responsible for several trade shows and a large annual meeting. Attendance was good for many years, and she and her staff focused their efforts on creating an excellent meeting experience (program plus venue). Recently, however, there has been declining response to promotions, and a simultaneous decline in attendance. Is data mining right for Donna and her organization?

Economics - Begin with economics - Is there a pressing business need? Donna knows that meeting attendance was down 15% this year. If that trend continues for two more years, turnout will be only about 60% of its previous level (85% x 85% x 85%), and she knows that the annual meeting is not sustainable at that level. It is critical, then, to improve the attendance, but to do so profitably. Yes, Donna has an economic need.

Generally speaking, data mining can address a wide variety of business "pains". If your company is experiencing rapid growth, DM can identify promising new retail locations or find more prospects for your online service. Conversely, if your organization is facing declining sales, DM can improve retention or identify your best existing customers for cross-selling and upselling. It is not advisable, however, to start a data mining effort without explicitly identifying a critical business need. Vast sums have been spent wastefully on mining data for "nuggets" of knowledge that have little or no value to the enterprise.

Data - Next, consider your data assets - Are sufficient, relevant data available? Donna has a spreadsheet that captures several years of meeting registrations (who attended). She also maintains a promotion history (who was sent a meeting invitation) in a simple database. So, information is available about the stimulus (sending invitations) and the response (did/did not attend). This data is clearly relevant to understanding and improving future attendance.

Donna's multi-year registration spreadsheet contains about 10,000 names. The promotion history database is even larger because many invitations are sent for each meeting, both to prior attendees and to prospects who have never attended. Sounds like plenty of data, but to be sure, it is useful to think about the factors that might be predictive of future attendance. Donna consults her intuitive knowledge of the meeting participants and lists four key factors:

    attended previously
    age
    size of company
    industry

To get a reasonable estimate for the amount of data required, we can use the following rule of thumb, developed from many years of experience:

Number of records needed ≥ 60 x 2^N (where N is the number of factors)

Since Donna listed 4 key factors, the above formula estimates that she needs 960 records (60 x 2^4 = 60 x 16). Since she has more than 10,000, we conclude Yes, Donna has relevant and sufficient data for DM.

More generally, in considering your own situation, it is important to have data that represents:

    stimulus and response (what was done and what happened)
    positive and negative outcomes

Simply put, you need data on both what works and what doesn't.

Performance - Finally, performance - Is a moderate improvement required relative to current benchmarks? Donna would like to increase attendance back to its previous level without increasing her promotion costs. She determines that the response rate to promotions needs to increase from 2% to 2.5% to meet her goals. In data mining terms, a moderate improvement is generally in the range of 10% to 100%. Donna's need is in this interval, at 25%. For her, Yes, a moderate performance increase is needed.

The performance question is typically the hardest one to address prior to starting a project. Performance is an outcome of the data mining effort, not a precursor to it. There are no guarantees, but we can use past experience as a guide. As noted for Donna above, incremental-to-moderate improvements are reasonable to expect with data mining. But don't expect DM to produce a miracle.

Conclusion

Summarizing, to determine if data mining fits your organization, you must consider:

    your business need
    your available data assets
    the performance improvement required

In the case study, Donna answered yes to each of the questions posed. She is well-positioned to proceed with a data mining project. You, too, can apply the same thought process before you spend a single dollar on DM. If you decide there is a fit, this preparation will serve you well in talking with your staff, vendors, and consultants who can help you move a data mining project forward.



Source: http://ezinearticles.com/?Data-Mining-Questions?-Some-Back-Of-The-Envelope-Answers&id=6047713

Searching the Web Using Text Mining and Data Mining

There are many types of financial analysis tools that are useful for various purposes. Most of these are easily available online. Two such tools of software for financial analysis include the text mining and data mining. Both methods have been discussed in details in the following section.

The features of Text Mining It is a way by which information of high-quality can be derived from a text. It involves giving structure to the input text then deriving patterns within the data that has been structured. Finally, the process of evaluating and interpreting the output is undertaken.

This form of mining usually involves the process of structuring the text input, and deriving patterns within the structured data, and finally evaluating and interpreting the data. It differs from the way we are familiar with in searching the web. The goal of this method is to find unknown information. It can be done with analyses in topics that that were not researched before.

What is Data Mining? It is the process of the extraction of patterns from the data. Nowadays, it has become very vital to transform this data into information. It is particularly used in marketing practices as well as fraud detection and surveillance. We can extract hidden information from huge databases of information. It can be used to predict future trends as well as to aid the company business to make knowledgeable quick decisions.

Working of data mining: Modeling technique is used to perform the operation of such form of mining. For these techniques, you must need to be fully integrated with a data warehouse as well as financial analysis tools. Some of the areas where this method is used are:

    Pharmaceutical companies which need to analyze its sales force and to achieve their targets.
    Credit card companies and transportation companies with sales force.
    Also large consumer goods companies use such mining techniques.
    With this method, a retailer may utilize POS or point-of-sale data of customer purchases in order to develop strategies for sale promotion.

The major elements of Data mining:

1. Extracting, transforming, and sending load transaction data on the data warehouse of the server system.

2. Storing and managing the data in for database systems that are multidimensional in nature.

3. Presenting data to the IT professionals and business analysts for processing.

4. Presenting the data to the application software for analyses.

5. Presentation of the data in dynamic ways like graph or table.

The main point of difference between the two types of mining is that text mining checks the patterns from natural text instead of databases where the data is structured.

Data mining software supports the entire process of such mining and discovery of knowledge. These are available on the internet. Data mining software serves as one of the best financial analysis tools. You can avail of data mining software suites and their reviews freely over the internet and easily compare between them.



Source: http://ezinearticles.com/?Searching-the-Web-Using-Text-Mining-and-Data-Mining&id=5299621

Monday, 2 September 2013

An Easy Way For Data Extraction

There are so many data scraping tools are available in internet. With these tools you can you download large amount of data without any stress. From the past decade, the internet revolution has made the entire world as an information center. You can obtain any type of information from the internet. However, if you want any particular information on one task, you need search more websites. If you are interested in download all the information from the websites, you need to copy the information and pate in your documents. It seems a little bit hectic work for everyone. With these scraping tools, you can save your time, money and it reduces manual work.

The Web data extraction tool will extract the data from the HTML pages of the different websites and compares the data. Every day, there are so many websites are hosting in internet. It is not possible to see all the websites in a single day. With these data mining tool, you are able to view all the web pages in internet. If you are using a wide range of applications, these scraping tools are very much useful to you.

The data extraction software tool is used to compare the structured data in internet. There are so many search engines in internet will help you to find a website on a particular issue. The data in different sites is appears in different styles. This scraping expert will help you to compare the date in different site and structures the data for records.

And the web crawler software tool is used to index the web pages in the internet; it will move the data from internet to your hard disk. With this work, you can browse the internet much faster when connected. And the important use of this tool is if you are trying to download the data from internet in off peak hours. It will take a lot of time to download. However, with this tool you can download any data from internet at fast rate.There is another tool for business person is called email extractor. With this toll, you can easily target the customers email addresses. You can send advertisement for your product to the targeted customers at any time. This the best tool to find the database of the customers.

However, there are some more scraping tolls are available in internet. And also some of esteemed websites are providing the information about these tools. You download these tools by paying a nominal amount.



Source: http://ezinearticles.com/?An-Easy-Way-For-Data-Extraction&id=3517104

Sunday, 1 September 2013

Outsourcing Data Entry and Data Conversion Services

Data Entry is one such aspects of any business that needs to be handled properly for expanding your business. Online Form Entry Services is one of the leading elements for running a business successfully. Online form entry services are ideally suited to high volume form entry applications such as CD-ROM publication, surveys and questionnaire, database and mailing list compilation, litigation support, electronic publication and multimedia system.

Form Entry plays vital role in every business area. Accumulated data is a powerful management resource. Online entry services cover most business and professional activities, including data conversion, image entry, document and image processing, catalog processing, image enhancement, image editing, and photo manipulation.

In this competitive world, data processing and storage of data in multiple formats is of great essence to every business. It makes the accessibility of data whenever it is needed. Sometimes it becomes headache, but Data conversion services are used to avoid such circumstances.

Data Conversion can be defined as the translation of data from one data format to other format.

Data conversion services include:

o Document conversion
o Book conversion
o CAD conversion
o PDF conversion
o XML/HTML/SGML conversion
o Catalog conversion
o Excel/Word/Email/Page Maker/DBF data format Services.

Affordable and Reliable form entry services provide numeric online entry, textual online entry, image entry, data format and also online data entry, offline data entry with strong quality and time bound. Form entry services also include data processing, image processing, forms processing, document processing, insurance claim processing, data mining and data cleansing services.

so, outsource your data entry work to reliable form entry provider and remove management headaches.



Source: http://ezinearticles.com/?Outsourcing-Data-Entry-and-Data-Conversion-Services&id=1357038