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/

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/

WP Web Scraper Review

WP Web Scraper is the Word Press plugin that works to extract web data into custom Word Press pages. The scraper uses a cURL extraction library for scraping and phpQuery for parsing HTML. This tool is a good reliable plugin among the other scraping software and plugins.
Plugin Usage

This scraper plugin can be inserted either into a WordPress theme or directly by the shortcode into the page HTML.

The shortcode use of the plugin is simple. Insert into the HTML page the plugin denotation:
[wрws url="..." selector="..."  {other optional arguments here} ]

For the PHP implementation insert the following tag into a template:
<?php echo wpws_get_content($url, $selector, $xpath, $wpwsopt)?>
Plugin features

The scraper plugin is rich in features, giving much more flexibility compared to its counterpart, Web Scraper Shortcode.

    Caching of scraped data is defined as a cache timeout in minutes.
    The scrape plugin allows one to customize a user-agent (see in example).
    Error handling is well elaborated with the plugin: silent fail, error display, custom error message or display expired cache (see in example).
    It allows one to clear or replace a regex pattern from extraction before output into the WordPress page (clear_regex, replace_regex parameters).
    A good feature of the plugin is having a basehref parameter. Basehref is a parameter which can be used to convert relative links from the extracted data into absolute links. For example, basehref=”http://yahoo.com”, will convert all relative links to absolute by appending http://yahoo.com to all href and scr values. Note: basehref needs to be a complete path (with http) with no trailing slash (see in example).
    It allows to pass POST arguments to a URL to be scraped.
    postargs=’name1=value1&name2=value2′
    The scrape plugin provides the means for the dynamic conversion of scrape data into specified character encoding (using incov) in order to scrape data from a site using a different charset.
    For advanced use, it can create scrape pages on the fly using dynamic generation of URLs to scrap or post arguments based on your page’s get or post arguments.
    It also has a callback function to be invoked for parsing the scraped data.

Example

An example of the use of the plugin.

    We want to extract a piece of html on this URL:
    http://ca.finance.yahoo.com/q?s=rab.v&ql=1
    append the base to the relative links:
    basehref=’http://ca.finance.yahoo.com’
    having a custom user-agent:
    user-agent=”bot at extract-web-data.com”
    switch error handling to on:
    on_error=”error_show”
    select the second child div of the element with id=’yfi_comparison’ :
    selector=”#yfi_comparison div:eq(1)”
    output result as HTML (by default) rather than a plain text:
    output=”html”

The result follows:
[wpws url='http://ca.finance.yahoo.com/q?s=rab.v&ql=1' basehref="http://ca.finance.yahoo.com" user_agent="bot at extract-web-data.com" on_error="error_show" selector="#yfi_comparison div:eq(1)"  ]

_________________________________
Note that since we’ve applied the basehref argument, the context links are full, not relative.

This scraper’s parameters array is dumped here:
[wpws url='http://ca.finance.yahoo.com/q?s=rab.v&ql=1' basehref="http://ca.finance.yahoo.com" user_agent="bot at extract-web-data.com" on_error="error_show" selector="#yfi_comparison div:eq(1)" output="html" ]
Decoding option

One may specify a charset for iconv charset conversion of scraped content through an htmldecode parameter. You need to specify the charset of the source URL you are scraping from. If ignored, the default encoding of your blog will be used.
Callback

Using the callback function, you can extend the plugin to do advanced parsing. Simply put, the callback function will parse the extracted value and return the required data. Your callback function can reside in the functions.php of your theme. The function will take a single string parameter, parse it and return a string as output.
Special notes about the scrape plugin

    Plugin does not work for more then 1 selector.
    Be cautious using the plugin since it stores the scraped pages in the temporary wp-options table (MySQL database). So the problem is that the plugin does not take care of flushing those intermediate data. If you intend to extract large data chunks this table might grow dangerously large to put down MySQL.

Summary

This plugin is a convenient tool for a fast scrape of dynamic web data. It provides much flexibility as to sifting results, appending for relative links, callback function call and others. I would recommend it for miscellaneous data-rich web page development.



Source: http://extract-web-data.com/wp-web-scraper-review/

Outsource Data Mining Services to Offshore Data Entry Company

Companies in India offer complete solution services for all type of data mining services.

Data Mining Services and Web research services offered, help businesses get critical information for their analysis and marketing campaigns. As this process requires professionals with good knowledge in internet research or online research, customers can take advantage of outsourcing their Data Mining, Data extraction and Data Collection services to utilize resources at a very competitive price.

In the time of recession every company is very careful about cost. So companies are now trying to find ways to cut down cost and outsourcing is good option for reducing cost. It is essential for each size of business from small size to large size organization. Data entry is most famous work among all outsourcing work. To meet high quality and precise data entry demands most corporate firms prefer to outsource data entry services to offshore countries like India.

In India there are number of companies which offer high quality data entry work at cheapest rate. Outsourcing data mining work is the crucial requirement of all rapidly growing Companies who want to focus on their core areas and want to control their cost.

Why outsource your data entry requirements?

Easy and fast communication: Flexibility in communication method is provided where they will be ready to talk with you at your convenient time, as per demand of work dedicated resource or whole team will be assigned to drive the project.

Quality with high level of Accuracy: Experienced companies handling a variety of data-entry projects develop whole new type of quality process for maintaining best quality at work.

Turn Around Time: Capability to deliver fast turnaround time as per project requirements to meet up your project deadline, dedicated staff(s) can work 24/7 with high level of accuracy.

Affordable Rate: Services provided at affordable rates in the industry. For minimizing cost, customization of each and every aspect of the system is undertaken for efficiently handling work.

Outsourcing Service Providers are outsourcing companies providing business process outsourcing services specializing in data mining services and data entry services. Team of highly skilled and efficient people, with a singular focus on data processing, data mining and data entry outsourcing services catering to data entry projects of a varied nature and type.

Why outsource data mining services?

360 degree Data Processing Operations
Free Pilots Before You Hire
Years of Data Entry and Processing Experience
Domain Expertise in Multiple Industries
Best Outsourcing Prices in Industry
Highly Scalable Business Infrastructure
24X7 Round The Clock Services

The expertise management and teams have delivered millions of processed data and records to customers from USA, Canada, UK and other European Countries and Australia.

Outsourcing companies specialize in data entry operations and guarantee highest quality & on time delivery at the least expensive prices.

Herat Patel, CEO at 3Alpha Dataentry Services possess over 15+ years of experience in providing data related services outsourced to India.

Visit our Facebook Data Entry profile for comments & reviews.

Our services helps to convert any kind of  hard copy sources, our data mining services helps to collect business contacts, customer contact, product specifications etc., from different web sources. We promise to deliver the best quality work and help you excel in your business by focusing on your core business activities. Outsource data mining services to India and take the advantage of outsourcing and save cost.



Source: http://ezinearticles.com/?Outsource-Data-Mining-Services-to-Offshore-Data-Entry-Company&id=4027029

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

Digitize Data With Data Processing Services

Unorganized data might cost you your numero UNO position in your domain. If you have well-organized data, it will not only be helpful in decision-making but will also guarantee a smooth flow of your business. If you are stuck with heaps of documents to be converted into electronic format. Then, outsourcing your files to a company providing Large Volume Data Processing Services is the most accurate and efficient option.

Data processing is the process in which computer programs and other processing systems are used to analyze, summarize and convert the data into an electronic format.

It involves a series of process which are: -

    Validation - This process checks that whether the entries are correct or not.
    Sorting - In this process, sorting is done either sequentially or in various sets.
    Summarize data - This process summarizes the data into main points.
    Aggregation - Combination of different fragments of records takes place in this process.
    Analysis - This process involves the analysis, interpretation and presentation of the collected and organized data.

Data processing companies have comprehensive knowledge about all the above mentioned steps and will provide a complete package of Large volume data processing services which includes: -

    Manual data entry
    Forms based data capture
    Full text data capture
    Digitization
    Document conversion
    Word Processing
    e-Book conversion
    Data extraction from web
    OCR- Optical character recognition

By outsourcing, you can get rid of large volumes of data pretty quickly and can lay more stress on core business activities.

You will have access to many other benefits like: -

    Heaps of cluttered and unorganized work will be organized, sorted and digitized.
    You can make use of neatly organized data to make informed business decisions.
    Chances of losing data will be scarce once it is digitized.
    You can do away with unwanted data and get access to relevant data.
    You can cut down the operating costs and need not incur any expenses in setting up infrastructure.
    You can get the data converted into a form of your choice.

Companies that deal with Large volume data processing services have the experience, expertise, manpower and technology to deliver results as per your expectations. They can handle your bulk of data easily and process it in your desired format within the deadline.

If you want your large volume of data to be digitized with accuracy and at cost-effective rates, choose an outsourcing company which has years of experience in providing Large volume data processing services. You just need to spend a few hours browsing on the net and then short-listing the prospectives. Once you are done with going through the portfolio of these firms and are contented with their information, you can negotiate the rate with them and stipulate the time.

This article about large volume data Processing services has been authored by Sam Efron. He is an experienced technical content writer from data-entry-india.com. With several years of experience and expertise of writing about Data Processing Services, he brings a seasoned maturity and knowledge to his articles.




Source: http://ezinearticles.com/?Digitize-Data-With-Data-Processing-Services&id=7963690

Data Mining - Efficient in Detecting and Solving the Fraud Cases

Data mining can be considered to be the crucial process of dragging out accurate and probably useful details from the data. This application uses analytical as well as visualization technology in order to explore and represent content in a specific format, which is easily engulfed by a layman. It is widely used in a variety of profiling exercises, such as detection of fraud, scientific discovery, surveys and marketing research. Data management has applications in various monetary sectors, health sectors, bio-informatics, social network data research, business intelligence etc. This module is mainly used by corporate personals in order to understand the behavior of customers. With its help, they can analyze the purchasing pattern of clients and can thus expand their market strategy. Various financial institutions and banking sectors use this module in order to detect the credit card fraud cases, by recognizing the process involved in false transactions. Data management is correlated to expertise and talent plays a vital role in running such kind of function. This is the reason, why it is usually referred as craft rather than science.

The main role of data mining is to provide analytical mindset into the conduct of a particular company, determining the historical data. For this, unknown external events and fretful activities are also considered. On the imperious level, it is more complicated mainly for regulatory bodies for forecasting various activities in advance and taking necessary measures in preventing illegal events in future. Overall, data management can be defined as the process of extracting motifs from data. It is mainly used to unwrap motifs in data, but more often, it is carried out on samples of the content. And if the samples are not of good representation then the data mining procedure will be ineffective. It is unable to discover designs, if they are present in the larger part of data. However, verification and validation of information can be carried out with the help of such kind of module.




Source: http://ezinearticles.com/?Data-Mining---Efficient-in-Detecting-and-Solving-the-Fraud-Cases&id=4378613

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

Usefulness of Web Scraping Services

For any business or organization, surveys and market research play important roles in the strategic decision-making process. Data extraction and web scraping techniques are important tools that find relevant data and information for your personal or business use. Many companies employ people to copy-paste data manually from the web pages. This process is very reliable but very costly as it results to time wastage and effort. This is so because the data collected is less compared to the resources spent and time taken to gather such data.

Nowadays, various data mining companies have developed effective web scraping techniques that can crawl over thousands of websites and their pages to harvest particular information. The information extracted is then stored into a CSV file, database, XML file, or any other source with the required format. After the data has been collected and stored, data mining process can be used to extract the hidden patterns and trends contained in the data. By understanding the correlations and patterns in the data; policies can be formulated and thereby aiding the decision-making process. The information can also be stored for future reference.

The following are some of the common examples of data extraction process:

• Scrap through a government portal in order to extract the names of the citizens who are reliable for a given survey.
• Scraping competitor websites for feature data and product pricing
• Using web scraping to download videos and images for stock photography site or for website design

Automated Data Collection
It is important to note that web scraping process allows a company to monitor the website data changes over a given time frame. It also collects the data on a routine basis regularly. Automated data collection techniques are quite important as they help companies to discover customer trends and market trends. By determining market trends, it is possible to understand the customer behavior and predict the likelihood of how the data will change.

The following are some of the examples of the automated data collection:

• Monitoring price information for the particular stocks on hourly basis
• Collecting mortgage rates from the various financial institutions on the daily basis
• Checking on weather reports on regular basis as required

By using web scraping services it is possible to extract any data that is related to your business. The data can then be downloaded into a spreadsheet or a database for it to be analyzed and compared. Storing the data in a database or in a required format makes it easier for interpretation and understanding of the correlations and for identification of the hidden patterns.

Through web scraping it is possible to get quicker and accurate results and thus saving many resources in terms of money and time. With data extraction services, it is possible to fetch information about pricing, mailing, database, profile data, and competitors data on a consistent basis. With the emergence of professional data mining companies outsourcing your services will greatly reduce your costs and at the same time you are assured of high quality services.




Source: http://ezinearticles.com/?Usefulness-of-Web-Scraping-Services&id=7181014

Customer Relationship Management (CRM) Using Data Mining Services

In today's globalized marketplace Customer relationship management (CRM) is deemed as crucial business activity to compete efficiently and outdone the competition. CRM strategies heavily depend on how effectively you can use the customer information in meeting their needs and expectations which in turn leads to more profit.

Some basic questions include - what are their specific needs, how satisfied they are with your product or services, is there a scope of improvement in existing product/service and so on. For better CRM strategy you need a predictive data mining models fueled by right data and analysis. Let me give you a basic idea on how you can use Data mining for your CRM objective.

Basic process of CRM data mining includes:
1. Define business goal
2. Construct marketing database
3. Analyze data
4. Visualize a model
5. Explore model
6. Set up model & start monitoring

Let me explain last three steps in detail.

Visualize a Model:
Building a predictive data model is an iterative process. You may require 2-3 models in order to discover the one that best suit your business problem. In searching a right data model you may need to go back, do some changes or even change your problem statement.

In building a model you start with customer data for which the result is already known. For example, you may have to do a test mailing to discover how many people will reply to your mail. You then divide this information into two groups. On the first group, you predict your desired model and apply this on remaining data. Once you finish the estimation and testing process you are left with a model that best suits your business idea.

Explore Model:
Accuracy is the key in evaluating your outcomes. For example, predictive models acquired through data mining may be clubbed with the insights of domain experts and can be used in a large project that can serve to various kinds of people. The way data mining is used in an application is decided by the nature of customer interaction. In most cases either customer contacts you or you contact them.

Set up Model & Start Monitoring:
To analyze customer interactions you need to consider factors like who originated the contact, whether it was direct or social media campaign, brand awareness of your company, etc. Then you select a sample of users to be contacted by applying the model to your existing customer database. In case of advertising campaigns you match the profiles of potential users discovered by your model to the profile of the users your campaign will reach.

In either case, if the input data involves income, age and gender demography, but the model demands gender-to-income or age-to-income ratio then you need to transform your existing database accordingly.




Source: http://ezinearticles.com/?Customer-Relationship-Management-%28CRM%29-Using-Data-Mining-Services&id=4641198

Data Extraction Services - A Helpful Hand For Large Organization

The data extraction is the way to extract and to structure data from not structured and semi-structured electronic documents, as found on the web and in various data warehouses. Data extraction is extremely useful for the huge organizations which deal with considerable amounts of data, daily, which must be transformed into significant information and be stored for the use this later on.

Your company with tons of data but it is difficult to control and convert the data into useful information. Without right information at the right time and based on half of accurate information, decision makers with a company waste time by making wrong strategic decisions. In high competing world of businesses, the essential statistics such as information customer, the operational figures of the competitor and the sales figures inter-members play a big role in the manufacture of the strategic decisions. It can help you to take strategic business decisions that can shape your business' goals..

Outsourcing companies provide custom made services to the client's requirements. A few of the areas where it can be used to generate better sales leads, extract and harvest product pricing data, capture financial data, acquire real estate data, conduct market research , survey and analysis, conduct product research and analysis and duplicate an online database..

The different types of Data Extraction Services:

    Database Extraction:
    Reorganized data from multiple databases such as statistics about competitor's products, pricing and latest offers and customer opinion and reviews can be extracted and stored as per the requirement of company.
    Web Data Extraction:
    Web Data Extraction is also known as data Extraction which is usually referred to the practice of extract or reading text data from a targeted website.

Businesses have now realized about the huge benefits they can get by outsourcing their services. Then outsourcing is profitable option for business. Since all projects are custom based to suit the exact needs of the customer, huge savings in terms of time, money and infrastructure are among the many advantages that outsourcing brings.

Advantages of Outsourcing Data Extraction Services:

    Improved technology scalability
    Skilled and qualified technical staff who are proficient in English
    Advanced infrastructure resources
    Quick turnaround time
    Cost-effective prices
    Secure Network systems to ensure data safety
    Increased market coverage

By outsourcing, you can definitely increase your competitive advantages. Outsourcing of services helps businesses to manage their data effectively, which in turn would enable them to experience an increase in profits.




Source: http://ezinearticles.com/?Data-Extraction-Services---A-Helpful-Hand-For-Large-Organization&id=2477589

Business Uses For Data Mining

When used wisely within Customer Relationship Management applications data mining can significantly improve the bottom line. It will end the process of randomly contacting a prospective or current customer through a call centre or by mailshot. With the effective use of data mining a company can concentrate its efforts on targeting prospects that have a high likelihood of being open to an offer. This in turn gives the ability for more sophisticated methods to be used such as campaigns being optimised to individuals.

Businesses that employ data mining techniques will usually see a high return on investment, but will also find that the number of predictive models can quickly increase. Rather than just implementing one model to predict which customers will respond positively, a business could build a different models for each region and customer type. Then instead of sending an offer to all prospects it may only want to send to prospects that have a high chance of taking up the offer. It may also want to determine which customers are going to be profitable during a certain time frame and direct their efforts towards them. To be able to maintain this quantity and quality of models, these model versions have to be well managed and automated data mining implemented.

Human Resources departments can also make a valid case for using data mining. It will allow them to in identifying the characteristics of their most successful employees. Information gained from such as resource can help HR focus their recruiting efforts accordingly.

Another example of data mining, is that used in retail. Often called market basket analysis, it is, for example, when a store records the purchases of customers, it could identify those customers who favour silk shirts over cotton ones; or customers who bought certain grocery items would also also buy the same specific item as well. This is often highlighted in on-line stores when you are told that so many people who bought a certain book or CD also bought XX as well.

Although some explanations of relationships may be difficult, taking advantage of it is easier. The example deals with association rules within transaction-based data. Not all data are transaction based and logical or inexact rules may also be present within a database. In a manufacturing application, an inexact rule may state that 73% of products which have a specific defect or problem will develop a secondary problem within the next six months.




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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.



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Various Data Mining Techniques

Also called Knowledge Discover in Databases (KDD), data mining is the process of automatically sifting through large volumes of data for patterns, using tools such as clustering, classification, association rule mining, and many more. There are several major data mining techniques developed and known today, and this article will briefly tackle them, along with tools for increased efficiency, including phone look up services.

Classification is a classic data mining technique. Based on machine learning, it is used to classify each item on a data set into one of predefined set of groups or classes. This method uses mathematical techniques, like linear programming, decision trees, neural network, and statistics. For instance, you can apply this technique in an application that predicts which current employees will most probably leave in the future, based on the past records of those who have resigned or left the company.

Association is one of the most used techniques, and it is where a pattern is discovered basing on a relationship of a specific item on other items within the same transaction. Market basket analysis, for example, uses association to figure out what products or services are purchased together by clients. Businesses use the data produced to devise their marketing campaign.

Sequential patterns, too, aim to discover similar patterns in data transaction over a given business phase or period. These findings are used for business analysis to see relationships among data.

Clustering makes useful cluster of objects that maintain similar characteristics using an automatic method. While classification assigns objects into predefined classes, clustering defines the classes and puts objects in them. Predication, on the other hand, is a technique that digs into the relationship between independent variables and between dependent and independent variables. It can be used to predict profits in the future - a fitted regression curve used for profit prediction can be drawn from historical sale and profit data.

Of course, it is highly important to have high-quality data in all these data mining techniques. A multi-database web service, for instance, can be incorporated to provide the most accurate telephone number lookup. It delivers real-time access to a range of public, private, and proprietary telephone data. This type of phone look up service is fast-becoming a defacto standard for cleaning data and it communicates directly with telco data sources as well.

Phone number look up web services - just like lead, name, and address validation services - help make sure that information is always fresh, up-to-date, and in the best shape for data mining techniques to be applied.

Equip your business with better leads and get better conversion rates by using phone look up and similar real-time web services.




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Unleash the Hidden Potential of Your Business Data With Data Mining and Extraction Services

Every business, small or large, is continuously amassing data about customers, employees and nearly every process in their business cycle. Although all management staff utilize data collected from their business as a basis for decision making in areas such as marketing, forecasting, planning and trouble-shooting, very often they are just barely scratching the surface. Manual data analysis is time-consuming and error-prone, and its limited functions result in the overlooking of valuable information that improve bottom-lines. Often, the sheer quantity of data prevents accurate and useful analysis by those without the necessary technology and experience. It is an unfortunate reality that much of this data goes to waste and companies often never realize that a valuable resource is being left untapped.

Automated data mining services allow your company to tap into the latent potential of large volumes of raw data and convert it into information that can be used in decision-making. While the use of the latest software makes data mining and data extraction fast and affordable, experienced professional data analysts are a key part of the data mining services offered by our company. Making the most of your data involves more than automatically generated reports from statistical software. It takes analysis and interpretation skills that can only be performed by experienced data analysis experts to ensure that your business databases are translated into information that you can easily comprehend and use in almost every aspect of your business.

Who Can Benefit From Data Mining Services?

If you are wondering what types of companies can benefit from data extraction services, the answer is virtually every type of business. This includes organizations dealing in customer service, sales and marketing, financial products, research and insurance.

How is Raw Data Converted to Useful Information?

There are several steps in data mining and extraction, but the most important thing for you as a business owner is to be assured that, throughout the process, the confidentiality of your data is our primary concern. Upon receiving your data, it is converted into the necessary format so that it can be entered into a data warehouse system. Next, it is compiled into a database, which is then sifted through by data mining experts to identify relevant data. Our trained and experienced staff then scan and analyze your data using a variety of methods to identify association or relationships between variables; clusters and classes, to identify correlations and groups within your data; and patterns, which allow trends to be identified and predictions to be made. Finally, the results are compiled in the form of written reports, visual data and spreadsheets, according to the needs of your business.

Our team of data mining, extraction and analyses experts have already helped a great number of businesses to tap into the potential of their raw data, with our speedy, cost-efficient and confidential services. Contact us today for more information on how our data mining and extraction services can help your business.



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What's Your Excuse For Not Using Data Mining?

In an earlier article I briefly described how data mining and RFM analysis can help marketers be more efficient (read... increased marketing ROI!). These marketing analytics tools can significantly help with all direct marketing efforts (multichannel campaign management efforts using direct mail, email and call center) and some interactive marketing efforts as well. So, why aren't all companies using it today? Well, typically it comes down to a lack of data and/or statistical expertise. Even if you don't have data mining expertise, YOU can benefit from data mining by using a consultant. With that in mind, let's tackle the first problem -- collecting and developing the data that is useful for data mining.

The most important data to collect for data mining include:

oTransaction data - For every sale, you at least need to know the product and the amount and date of the purchase.

oPast campaign response data - For every campaign you've run, you need to identify who responded and who didn't. You may need to use direct and indirect response attribution.

oGeo-demographic data - This is optional, but you may want to append your customer file/database with consumer overlay data from companies like Acxiom.

oLifestyle data - This is also an optional append of indicators of socio-economic lifestyle that are developed by companies like Claritas. All of the above data may or may not exist in the same data source. Some companies have a single holistic view of the customer in a database and some don't. If you don't, you'll have to make sure all data sources that contain customer data have the same customer ID/key. That way, all of the needed data can be brought together for data mining.

How much data do you need for data mining? You'll hear many different answers, but I like to have at least 15,000 customer records to have confidence in my results.

Once you have the data, you need to massage it to get it ready to be "baked" by your data mining application. Some data mining applications will automatically do this for you. It's like a bread machine where you put in all the ingredients -- they automatically get mixed, the bread rises, bakes, and is ready for consumption! Some notable companies that do this include KXEN, SAS, and SPSS. Even if you take the automated approach, it's helpful to understand what kinds of things are done to the data prior to model building.

Preparation includes:

oMissing data analysis. What fields have missing values? Should you fill in the missing values? If so, what values do you use? Should the field be used at all?

oOutlier detection. Is "33 children in a household" extreme? Probably - and consequently this value should be adjusted to perhaps the average or maximum number of children in your customer's households.

oTransformations and standardizations. When various fields have vastly different ranges (e.g., number of children per household and income), it's often helpful to standardize or normalize your data to get better results. It's also useful to transform data to get better predictive relationships. For instance, it's common to transform monetary variables by using their natural logs.

oBinning Data. Binning continuous variables is an approach that can help with noisy data. It is also required by some data mining algorithms.

More to come on data mining for marketers in my next article.

Jim Stafford has worked for leading companies in the Marketing Automation space (BI, data mining, campaign management and eMarketing) for over 10 years. He has held roles of Director - Database Marketing Solutions, Pre-Sales Manager, Product Manager, and Solution Architect at companies like Aprimo, Group1 Software, SAS, Siebel, SPSS and Unica. Mr. Stafford has consistently helped sales teams meet or beat established sales targets. He was the principal pre-sales contributor to Siebel's second largest MA sale with General Motors. Jim has had considerable exposure to many verticals including: Financial Services, Hospitality & Entertainment, Automotive, Communications, and Utilities. He is a seasoned expert at discovery and knows key industry trends. Jim has an M.A. Degree in Economics from the University of Maryland and has been a frequent speaker at annual National Center for Database Marketing and Direct Marketing Associations events. Visit [http://www.staffordsbsg.com/] to learn more about Jim and his company's services.



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Data Mining for Dollars

The more you know, the more you're aware you could be saving. And the deeper you dig, the richer the reward.

That's today's data mining capsulation of your realization: awareness of cost-saving options amid logistical obligations.

According to global trade group Association for Information and Image Management (AIIM), fewer than 25% of organizations in North America and Europe are currently utilizing captured data as part of their business process. With high ease and low cost associated with utilization of their information, this unawareness is shocking. And costly.

Shippers - you're in prime position to benefit the most by data mining and assessing your electronically-captured billing records, by utilizing a freight bill processing provider, to realize and receive significant savings.

Whatever your volume, the more you know about your transportation options, throughout all modes, the easier it is to ship smarter and save. A freight bill processor is able to offer insight capable of saving you 5% - 15% annually on your transportation expenditures.

The University of California - Los Angeles states that data mining is the process of analyzing data from different perspectives and summarizing it into useful information - knowledge that can be used to increase revenue, cuts costs, or both. Data mining software is an analytical tool that allows investigation of data from many different dimensions, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations among dozens of fields in large relational databases. Practically, it leads you to noticeable shipping savings.

Data mining and subsequent reporting of shipping activity will yield discovery of timely, actionable information that empowers you to make the best logistics decisions based on carrier options, along with associated routes, rates and fees. This function also provides a deeper understanding of trends, opportunities, weaknesses and threats. Exploration of pertinent data, in any combination over any time period, enables you the operational and financial view of your functional flow, ultimately providing you significant cost savings.

With data mining, you can create a report based on a radius from a ship point, or identify opportunities for service or modal shifts, providing insight regarding carrier usage by lane, volume, average cost per pound, shipment size and service type. Performance can be measured based on overall shipping expenditures, variances from trends in costs, volumes and accessorial charges.

The easiest way to get into data mining of your transportation information is to form an alliance with a freight bill processor that provides this independent analytical tool, and utilize their unbiased technologies and related abilities to make shipping decisions that'll enable you to ship smarter and save.




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Effective Online Data Entry Services

The outsourcing market has many enthusiastic buyers who have paid a small amount to online data entry service providers. They carry the opinion that they have paid too low as against the work they have got done. Online services is helpful to a number of smaller business units who take these projects as their significant source of occupation.

Online data-entry services include data typing, product entry, web and mortgage research, data mining as well as extraction services. Service providers allot proficient workforce at your service who timely deliver best possible results. They have updated technology, guaranteeing 100% data security.

Few obvious benefits found by outsourcing online data entry:

    Business units receive quality online entry services from projects owners.
    Entering data is the first step for companies through which they get the understanding of the work that makes strategic decisions. The raw data represented by mere numbers soon turns to be a decision making factor accelerating the progress of the business.
    Systems used by these services are completely protected to maintain high level of security.
    As you increasingly obtain high quality of information the business executive of the company is expected to arrive at extraordinary decisions which influence progress in the company.
    Shortened turnaround time.
    Cutting down on cost by saving on operational overheads.

Companies are highly fascinated by the benefits of outsourcing your projects for these services, as it saves time as well as money.

Flourishing companies want to concentrate on their key business activities instead of exploring into such non-key business activities. They take a wise step of outsourcing their work to data-entry-services and keep themselves free for their core business functions.




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Data Entry Services Are Meant To Ease Your Workload

Data entry services provided by the firms are growing very rapidly with a huge demand. It may sound that data entry is a simple task to do but it is not so simple and plays an important role in running a successful business. We all know that data and information related to any company is very crucial for them. Data are priceless for any firm, no-matter they are small or big. The companies provide you highly customized business solutions depending on your requirement.

The companies also provide various range of services for all kinds of textual data capturing from printed matter, manuscripts, and even web research. Very advanced technologies are used to convert large quantities of paper work and image based task to electronic data that is usable in database and in the management system. Any kind of data is very essential for an organization whether it is manual or electronic.

There are many companies that provide highly accurate data entry services with complete confidentiality and high level of accuracy. These services are undertaken by banks, retail organizations, medical research facilities, universities, insurance companies, newspapers, large corporate enterprises, direct marketing and database marketing firms, school and trade associations to make their organization a successful and profitable enterprise.

Outsourcing is a business strategy which is highly being used by businesses to take care of the data entry services. In fact, the process of outsourcing has made things simpler for business owners and the businesses are running successfully. The companies that are involved in outsourcing work do provide these services efficiently to those firms who are burdened with heavy workload. If you are running a business of your own and want to manage it properly and run smoothly, then all you need to do is to hire data entry services.

Availing the benefits of outsourcing works in the form of data entry services can prove tremendous for your company. If you outsource your extra burden of work to a company then in such case, you can make growth plans and strategies for your organization. The companies will console you about the high quality of services and the accuracy they provide for the business that needs data to be extracted from any source.

Data entry services is an information technology enabled services that provides you wide range of services. The professionals working for you are trained and extremely talented who are ready to provide you high end services with full dedication. Since, you are spending money for this, so you must take the best services and choose those companies who can cater to your needs according to you.

Data entry services is not a complex application but it's extremely time taking and this the main reason for a company that hires this service so that they can save their time and money. Every business has many more things to consider for their growth prospects and for this reason they don't want to waste their time and money in such stuffs. The professionals are especially trained according to the requirement of the work depending on how critical the work is. Hiring for this service is definitely a wise decision for your business prospects. These types of services will surely help you to make big profits in the business. The strategy and techniques applied to any business is the key to success.



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