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/

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

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/

Effectiveness of Web Data Mining Through Web Research

Web data mining is systematic approach to keyword based and hyperlink based web research for gaining business intelligence. It requires analytical skills to understand hyperlink structure of given website. Hyperlinks possess enormous amount of hidden human annotations that can help automatically understand the authority. If the webmaster provides a hyperlink pointing to another website or web page, this action is perceived as an endorsement to that webpage. Search engines highly focus on such endorsements to define the importance of the page and place them higher in organic search results.

However every hyperlink does not refer to the endorsement since the webmaster may have used it for other purposes, such as navigation or to render paid advertisements. It is important to note that authoritative pages rarely provide informative descriptions. For an instant, Google's homepage may not provide explicit self-description as "Web search engine."

These features of hyperlink systems have forced researchers to evaluate another important webpage category called hubs. A hub is a unique, informative webpage that offers collections of links to authorities. It may have only a few links pointing to other web pages but it links to a collection of prominent sites on a single topic. A hub directly awards authority status on sites that focus on a single topic. Typically, a quality hub points to many quality authorities, and, conversely, a web page that many such hubs link to can be deemed as a superior authority.

Such approach of identifying authoritative pages has resulted in the development of various popularity algorithms such as PageRank. Google uses PageRank algorithm to define authority of each webpage for a relevant search query. By analyzing hyperlink structures and web page content, these search engines can render better-quality search results than term-index engines such as Ask and topic directories such as DMOZ.




Source: http://ezinearticles.com/?Effectiveness-of-Web-Data-Mining-Through-Web-Research&id=5094403

Monday 23 September 2013

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.




Source: http://ezinearticles.com/?Unleash-the-Hidden-Potential-of-Your-Business-Data-With-Data-Mining-and-Extraction-Services&id=4642076

Friday 20 September 2013

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

Thursday 19 September 2013

Data Mining vs Screen-Scraping

Data mining isn't screen-scraping. I know that some people in the room may disagree with that statement, but they're actually two almost completely different concepts.

In a nutshell, you might state it this way: screen-scraping allows you to get information, where data mining allows you to analyze information. That's a pretty big simplification, so I'll elaborate a bit.

The term "screen-scraping" comes from the old mainframe terminal days where people worked on computers with green and black screens containing only text. Screen-scraping was used to extract characters from the screens so that they could be analyzed. Fast-forwarding to the web world of today, screen-scraping now most commonly refers to extracting information from web sites. That is, computer programs can "crawl" or "spider" through web sites, pulling out data. People often do this to build things like comparison shopping engines, archive web pages, or simply download text to a spreadsheet so that it can be filtered and analyzed.

Data mining, on the other hand, is defined by Wikipedia as the "practice of automatically searching large stores of data for patterns." In other words, you already have the data, and you're now analyzing it to learn useful things about it. Data mining often involves lots of complex algorithms based on statistical methods. It has nothing to do with how you got the data in the first place. In data mining you only care about analyzing what's already there.

The difficulty is that people who don't know the term "screen-scraping" will try Googling for anything that resembles it. We include a number of these terms on our web site to help such folks; for example, we created pages entitled Text Data Mining, Automated Data Collection, Web Site Data Extraction, and even Web Site Ripper (I suppose "scraping" is sort of like "ripping"). So it presents a bit of a problem-we don't necessarily want to perpetuate a misconception (i.e., screen-scraping = data mining), but we also have to use terminology that people will actually use.

Todd Wilson is the owner of screen-scraper.com (http://www.screen-scraper.com/), a company which specializes in data extraction from web pages. While not scraping screens Todd is hard at work finishing up a doctoral degree in Instructional Psychology and Technology.




Source: http://ezinearticles.com/?Data-Mining-vs-Screen-Scraping&id=146813

Tuesday 17 September 2013

Data Mining Basics

Definition and Purpose of Data Mining:

Data mining is a relatively new term that refers to the process by which predictive patterns are extracted from information.

Data is often stored in large, relational databases and the amount of information stored can be substantial. But what does this data mean? How can a company or organization figure out patterns that are critical to its performance and then take action based on these patterns? To manually wade through the information stored in a large database and then figure out what is important to your organization can be next to impossible.

This is where data mining techniques come to the rescue! Data mining software analyzes huge quantities of data and then determines predictive patterns by examining relationships.

Data Mining Techniques:

There are numerous data mining (DM) techniques and the type of data being examined strongly influences the type of data mining technique used.

Note that the nature of data mining is constantly evolving and new DM techniques are being implemented all the time.

Generally speaking, there are several main techniques used by data mining software: clustering, classification, regression and association methods.

Clustering:

Clustering refers to the formation of data clusters that are grouped together by some sort of relationship that identifies that data as being similar. An example of this would be sales data that is clustered into specific markets.

Classification:

Data is grouped together by applying known structure to the data warehouse being examined. This method is great for categorical information and uses one or more algorithms such as decision tree learning, neural networks and "nearest neighbor" methods.

Regression:

Regression utilizes mathematical formulas and is superb for numerical information. It basically looks at the numerical data and then attempts to apply a formula that fits that data.

New data can then be plugged into the formula, which results in predictive analysis.

Association:

Often referred to as "association rule learning," this method is popular and entails the discovery of interesting relationships between variables in the data warehouse (where the data is stored for analysis). Once an association "rule" has been established, predictions can then be made and acted upon. An example of this is shopping: if people buy a particular item then there may be a high chance that they also buy another specific item (the store manager could then make sure these items are located near each other).

Data Mining and the Business Intelligence Stack:

Business intelligence refers to the gathering, storing and analyzing of data for the purpose of making intelligent business decisions. Business intelligence is commonly divided into several layers, all of which constitute the business intelligence "stack."

The BI (business intelligence) stack consists of: a data layer, analytics layer and presentation layer.

The analytics layer is responsible for data analysis and it is this layer where data mining occurs within the stack. Other elements that are part of the analytics layer are predictive analysis and KPI (key performance indicator) formation.

Data mining is a critical part of business intelligence, providing key relationships between groups of data that is then displayed to end users via data visualization (part of the BI stack's presentation layer). Individuals can then quickly view these relationships in a graphical manner and take some sort of action based on the data being displayed.

Steve Bogdon is the Advertising director for Dashboard Insight, one of the fastest growing business intelligence (BI) sites on the web. Dashboard Insight is an authoritative and trusted online resource for the business intelligence, data visualization and dashboard software communities.




Source: http://ezinearticles.com/?Data-Mining-Basics&id=5120773

Monday 16 September 2013

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.





Source: http://ezinearticles.com/?Data-Mining-for-Dollars&id=7061178

Saturday 14 September 2013

The Benefits of Data Mining

Data mining can truly help a business reach its fullest potential. It is a way to assess how business is being affected by certain characteristics, and can help business owners increase their profits and avoid making business mistakes down the line. Essentially, through this process, a business is analyzing certain data from different perspectives in order to get a full rounded view of how their company is doing. Business owners can get a broad perspective on things such as customer trending, where they are losing money and where they are making money. The information can also reveal ways that can help a business cut unneeded costs and can help them increase their overall income.

Data mining software is one tool that can help a company assess and analyze their data in more efficient terms. It can be extremely user friendly and allow people to delve into their data from a variety of different angles and points of view. In more technical terms, data mining software allows you to see the correlations and patterns of one's own data compared with those across many other regional databases.

People have been using data mining for many years in different formats. Only since the technology has become available has data software been used. But there have been many ways in the past for companies to assess their data and use it to their advantage. By taking polls, or using store scanners, product codes and bar codes, people have been able to gather data, analyze it and use it to their advantage. But it cannot be denied that the availability of greater technology has greatly increased the ability to store or gather data, make predictions about outcomes and use customer trend reports to greater advantages. The ability to store infinite amounts of data has given business owners a great advantage and truly has helped increase sales and lower costs. This data mining has actually led to data being stored in data warehouses. In data warehouses, various organizations will integrate their mined data into one large data warehouse. The information accessible in data warehouses is available to further help companies reduce risk taking and integrate proper selling techniques to improve business.

Data mining also can allow companies to see where their best selling points are and give them the opportunity to take advantage of this information. For example, if a pharmacy places a display of lip balm at the cashier counter, data mining can detect how many people bought lip balm from the cashier counter rather people who bought the lip balm when it was placed at another point in the store. Data mining can determine where the most effective points of sale are throughout a store or if a certain promotion went well one time of the month, but did not go well at another time of the month. Companies can make offers based on the buying habits of their customers as well.

Data mining can truly help businesses reach their highest profitability by paying attention to customer trending.

Improving your overall business performance is never easy. However, new innovations in data mining software can increase your information forecasting capabilities and enhance your profit drivers as well!




Source: http://ezinearticles.com/?The-Benefits-of-Data-Mining&id=4565509

Friday 13 September 2013

Web Data Extraction Services and Data Collection Form Website Pages

For any business market research and surveys plays crucial role in strategic decision making. Web scrapping and data extraction techniques help you find relevant information and data for your business or personal use. Most of the time professionals manually copy-paste data from web pages or download a whole website resulting in waste of time and efforts.

Instead, consider using web scraping techniques that crawls through thousands of website pages to extract specific information and simultaneously save this information into a database, CSV file, XML file or any other custom format for future reference.

Examples of web data extraction process include:
• Spider a government portal, extracting names of citizens for a survey
• Crawl competitor websites for product pricing and feature data
• Use web scraping to download images from a stock photography site for website design

Automated Data Collection
Web scraping also allows you to monitor website data changes over stipulated period and collect these data on a scheduled basis automatically. Automated data collection helps you discover market trends, determine user behavior and predict how data will change in near future.

Examples of automated data collection include:
• Monitor price information for select stocks on hourly basis
• Collect mortgage rates from various financial firms on daily basis
• Check whether reports on constant basis as and when required

Using web data extraction services you can mine any data related to your business objective, download them into a spreadsheet so that they can be analyzed and compared with ease.

In this way you get accurate and quicker results saving hundreds of man-hours and money!

With web data extraction services you can easily fetch product pricing information, sales leads, mailing database, competitors data, profile data and many more on a consistent basis.




Source: http://ezinearticles.com/?Web-Data-Extraction-Services-and-Data-Collection-Form-Website-Pages&id=4860417

Thursday 12 September 2013

How Data Mining Can Help in Customer Relationship Management Or CRM?

Customer relationship management (CRM) is critical activity of improvising customer interactions while at the same time making the interactions more amicable through individualization. Data mining utilizes various data analysis and modeling methods to detect specific patterns and relationships in data. This helps in understanding what a customer wants and forecasting what they will do.

Using Data mining you can find out right prospects and offer them right products. This results in improved revenue because you can respond to each customer in best way using fewer resources.

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

Let me explain above steps in detail.

Define the business objective:
Every CRM process has one or more business objective for which you need to construct the suitable model. This model varies depending on your specific goal. The more precise your statement for defining the problem is the more successful is your CRM project.

Construct a marketing database:
This step involves creation of constructive marketing database since your operational data often don't contain the information in the form you want it. The first step in building your database is to clean it up so that you can construct clean models with accurate data.

The data you need may be scattered across different databases such as the client database, operational database and sales databases. This means you have to integrate the data into a single marketing database. Inaccurately reconciled data is a major source of quality issues.

Analyze the data:
Prior to building a correct predictive model, you must analyze your data. Collect a variety of numerical summaries (such as averages, standard deviations and so forth). You may want to generate a cross-section of multi-dimensional data such as pivot tables.

Graphing and visualization tools are a vital aid in data analysis. Data visualization most often provides better insight that leads to innovative ideas and success.




Source: http://ezinearticles.com/?How-Data-Mining-Can-Help-in-Customer-Relationship-Management-Or-CRM?&id=4572272

Tuesday 10 September 2013

Know What the Truth Behind Data Mining Outsourcing Service

We came to that, what we call the information age where industries are like useful data needed for decision-making, the creation of products - among other essential uses for business. Information mining and converting them to useful information is a part of this trend that allows companies to reach their optimum potential. However, many companies that do not meet even one deal with data mining question because they are simply overwhelmed with other important tasks. This is where data mining outsourcing comes in.

There have been many definitions to introduced, but it can be simply explained as a process that involves sorting through large amounts of raw data to extract valuable information needed by industries and enterprises in various fields. In most cases this is done by professionals, professional organizations and financial analysts. He has seen considerable growth in the number of sectors or groups that enter my self.
There are a number of reasons why there is a rapid growth in data mining outsourcing service subscriptions. Some of them are presented below:

A wide range of services

Many companies are turning to information mining outsourcing, because they cover a wide range of services. These services include, but are not limited to data from web applications congregation database, collect contact information from different sites, extract data from websites using the software, the sort of stories from sources news, information and accumulate commercial competitors.

Many companies fall

Many industries benefit because it is fast and realistic. The information extracted by data mining service providers of outsourcing used in crucial decisions in the field of direct marketing, e-commerce, customer relationship management, health, scientific tests and other experimental work, telecommunications, financial services, and a whole lot more.

A lot of advantages

Subscribe data mining outsourcing services it's offers many benefits, as providers assures customers to render services to world standards. They strive to work with improved technologies, scalability, sophisticated infrastructure, resources, timeliness, cost, the system safer for the security of information and increased market coverage.

Outsourcing allows companies to focus their core business and can improve overall productivity. Not surprisingly, information mining outsourcing has been a first choice of many companies - to propel the business to higher profits.



Source: http://ezinearticles.com/?Know-What-the-Truth-Behind-Data-Mining-Outsourcing-Service&id=5303589

Monday 9 September 2013

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

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

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

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

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

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

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

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

Frank Poladi is the author of this article about data mining in the 21st century. In this article he gives his readers insight on the world of data mining and using it with business intelligence solutions. He notes that to make sense of all this data enterprise reporting is a major factor as well.



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

Saturday 7 September 2013

Data Mining and the Tough Personal Information Privacy Sell Considered

Everyone come on in and have a seat, we will be starting this discussion a little behind schedule due to the fact we have a full-house here today. If anyone has a spare seat next to them, will you please raise your hands, we need to get some of these folks in back a seat. The reservations are sold out, but there should be a seat for everyone at today's discussion.

Okay everyone, I thank you and thanks for that great introduction, I just hope I can live up to all those verbal accolades.

Oh boy, not another controversial subject! Yes, well, surely you know me better than that by now, you've come to expect it. Okay so, today's topic is one about the data mining of; Internet Traffic, Online Searches, Smart Phone Data, and basically, storing all the personal data about your whole life. I know, you don't like this idea do you - or maybe you participate online in social online networks and most of your data is already there, and you've been loading up your blog with all sorts of information?

Now then, contemporary theory and real world observation of the virtual world predicts that for a fee, or for a trade in free services, products, discounts, or a chance to play in social online networks, employment opportunity leads, or the prospects of future business you and nearly everyone will give up some personal information.

So, once this data is collected, who will have access to it, who will use it, and how will they use it? All great questions, but first how can the collection of this data be sold to the users, and agreed upon in advance? Well, this can at times be very challenging; yes, very tough sell, well human psychology online suggests that if we give benefits people will trade away any given data of privacy.

Hold That Thought.

Let's digress a second, and have a reality check dialogue, and will come back to that point above soon enough, okay - okay agreed then.

The information online is important, and it is needed at various national security levels, this use of data is legitimate and worthy information can be gained in that regard. For instance, many Russian Spies were caught in the US using social online networks to recruit, make business contacts, and study the situation, makes perfect sense doesn't it? Okay so, that particular episode is either; an excuse to gather this data and analyze it, or it is a warning that we had better. Either way, it's a done deal, next topic.

And, there is the issue with foreign spies using the data to hurt American businesses, or American interests, or even to undermine the government, and we must understand that spies in the United States come from over 70 other nations. And let's not dismiss the home team challenge. What's that you ask? Well, we have a huge intelligence industrial complex and those who work in and around the spy business, often freelance on the side for Wall Street, corporations, or other interests. They have access to information, thus all that data mined data is at their disposal.

Is this a condemnation of sorts; No! I am merely stating facts and realities behind the curtain of created realities of course, without judgment, but this must be taken into consideration when we ask; who can we trust with all this information once it is collected, stored, and in a format which can be sorted? So, we need a way to protect this data for the appropriate sources and needs, without allowing it to be compromised - this must be our first order of business.

Let's Undigress and Go Back to the Original Topic at hand, shall we? Okay, deal.

Now then, what about large corporate collecting information; Proctor and Gamble, Ford, GM, Amazon, etc? They will certainly be buying this data from social networks, and in many cases you've already given up your rights to privacy merely by participating. Of course, all the data will help these companies refine their sorts using your preferences, thus, the products or services they pitch you will be highly targeted to your exact desires, needs, and demographics, which is a lot better than the current bombardment of Viagra Ads with disgusting titles, now in your inbox, deleted junk files.

Look, here is the deal...if we are going to collect data online, through social networks, and store all that the data, then we also need an excuse to collect the data first place, or the other option is not tell the public and collect it anyway, which we already probably realize that is now being done in some form or fashion. But let's for the sake of arguments say it isn't, then should we tell the public we are doing, or are going to do this. Yes, however if we do not tell the public they will eventually figure it out, and conspiracy theories will run rampant.

We already know this will occur because it has occurred in the past. Some say that when any data is collected from any individual, group, company, or agency, that all those involved should also be warned on all the collection of data, as it is being collected and by whom. Including the NSA, a government, or a Corporation which intends on using this data to either sell you more products, or for later use by their artificial intelligence data scanning tools.

Likewise, the user should be notified when cookies are being used in Internet searchers, and what benefits they will get, for instance; search features to help bring about more relevant information to you, which might be to your liking. Such as Amazon.com which tracks customer inquiries and brings back additional relevant results, most online shopping eCommerce sites do this, and there was a very nice expose on this in the Wall Street Journal recently.

Another digression if you will, and this one is to ask a pertinent question; If the government or a company collects the information, the user ought to know why, and who will be given access to this information in the future, so let's talk about that shall we? I thought you might like this side topic, good for you, it shows you also care about these things.

And as to that question, one theory is to use a system that allows certain trusted sources in government, or corporations which you do business with to see some data, then they won't be able to look without being seen, and therefore you will know which government agencies, and which corporations are looking at your data, and therefore there will be transparency, and there would have to be at that point justification for doing so. Or most likely folks would have a fit and then, a proverbial field day with the intrusion in the media.

Now then, one recent report from the government asks the dubious question; "How do we define the purpose for which the data will be used?"

Ah ha, another great question in this on-going saga indeed. It almost sounds as if they too were one of my concerned audience members, or even a colleague. Okay so, it is important not only to define the purpose of the data collection, but also to justify it, and it better be good. Hey, I see you are all smiling now. Good, because, it's going to get a bit more serious on some of my next points here.

Okay, and yes this brings about many challenges, and it is also important to note that there will be, ALWAYS more outlets for the data, which is collected, as time goes on. Therefore the consumer, investor, or citizen who allows their data to be compromised, stored for later use for important issues such as national security, or for corporations to help the consumer (in this case you) in their purchasing decisions, or for that company's planning for inventory, labor, or future marketing (most likely; again to whom; ha ha ha, yes you are catching on; You.

Thus, shouldn't you be involved at every step of the way; Ah, a resounding YES! I see from our audience today, and yes, I would have expected nothing less from you either. And as all this process takes place, eventually "YOU" are going to figure out that this data is out of control, and ends up everywhere. So, should you give away data easily?

No, and if it is that valuable, hold out for more. And then, you will be rewarded for the data, which is yours, that will be used on your behalf and potentially against you in some way in the future; even if it is only for additional marketing impressions on the websites you visit or as you walk down the hallway at the mall;

"Let's see a show of hands; who has seen Minority Report? Ah, most of you, indeed, if you haven't go see, it and you will understand what we are all saying up here, and others are saying in the various panel discussions this weekend."

Now you probably know this, but the very people who are working hard to protect your data are in fact the biggest purveyors of your information, that's right our government. And don't get me wrong, I am not anti-government, just want to keep it responsible, as much is humanly possible. Consider if you will all the data you give to the government and how much of that public record is available to everyone else;

    Tax forms to the IRS,
    Marriage licenses,
    Voting Registration,
    Selective Services Card,
    Property Taxes,
    Business Licenses,
    Etc.

The list is pretty long, and the more you do, the more information they have, and that means the more information is available; everywhere, about who; "YOU! That's who!" Good I am glad we are all clear on that one. Yes, indeed, all sorts of things, all this information is available at the county records office, through the IRS, or with various branches of OUR government. This is one reason we should all take notice to the future of privacy issues. Often out government, but it could be any first world government, claims it is protecting your privacy, but it has been the biggest purveyors of giving away our personal and private data throughout American history. Thus, there will a little bit of a problem with consumers, taxpayers, or citizens if they no longer trust the government for giving away such things as;

    Date of birth,
    Social Security number,
    Driver's license,
    Driving record,
    Taxable information,
    Etc., on and on.

And let's not kid ourselves here all this data is available on anyone, it's all on the web, much of it can be gotten free, some costs a little, never very much, and believe me there is a treasure trove of data on each one of us online. And that's before we look into all the other information being collected now.

Now then, here is one solution for the digital data realm, including smart phone communication data, perhaps we can control and monitor the packet flow of information, whereby all packets of info is tagged, and those looking at the data will also be tagged, with no exceptions. Therefore if someone in a government bureaucracy is looking at something they shouldn't be looking at, they will also be tagged as a person looking for the data.

Remember the big to do about someone going through Joe The Plumber's records in OH, or someone trying to release sealed documents on President Bush's DUI when he was in his 20s, or the fit of rage by Sara Palin when someone hacked her Yahoo Mail Account, or when someone at a Hawaii Hospital was rummaging through Barak Obama's certificate of showing up at the hospital as a baby, with mother in tow?

We need to know who is looking at the data, and their reason better be good, the person giving the data has a right-to-know. Just like the "right-to-know" laws at companies, if there are hazardous chemicals on the property. Let me speak on another point; Border Security. You see, we need to know both what is coming and going if we are to have secure borders.

You see, one thing they found with our border security is it is very important not only what comes over the border, which we do need to monitor, but it's also important to see what goes back over the border the other way. This is how authorities have been able to catch drug runners, because they're able to catch the underground economy and cash moving back to Mexico, and in holding those individuals, to find out whom they work for - just like border traffic - our information goes both ways, if we can monitor for both those ways, it keeps you happier, and our data safer.

Another question is; "How do we know the purpose for data being collected, and how can the consumer or citizen be sure that mass data releases will not occur, it's occurred in almost every agency, and usually the citizens are warned that their data was released or that the data base containing their information was breached, but that's after the fact, and it just proves that data is like water, and it's hard to contain. Information wants to be free, and it will always find a way to leak out, especially when it's in the midst of humans.

Okay, I see my time is running short here, let me go ahead and wrap it up and drive through a couple main points for you, then I'll open it up for questions, of which I don't doubt there will be many, that's good, and that means you've been paying attention here today.

It appears that we need to collect data for national security purposes research, planning, and for IT system for future upgrades. And collecting data for upgrades of an IT system, you really need to know about the bulk transfers of data and the time, which that data flows, and therefore it can be anonymized.

For national security issues, and for their research, that data will have anomalies in it, and there are problems with anomalies, because can project a false positives, and to get it right they have to continually refine it all. And although this may not sit well with most folks, nevertheless, we can find criminals this way, spies, terrorist cells, or those who work to undermine our system and stability of our nation.

With regards to government and the collection of data, we must understand that if there are bad humans in the world, and there are. And if many of those who shall seek power, may not be good people, and since information is power, you can see the problem, as that information and power will be used to help them promote their own agenda and rise in power, but it undermines the trust of the system of all the individuals in our society and civilization.

On the corporate front, they are going to try to collect as much data on you as they can, they've already started. After all, that's what the grocery stores are doing with their rewards program if you hadn't noticed. Not all the information they are collecting they will ever use, but they may sell it to third part affiliates, partners, or vendors, so that's at issue. Regulation will be needed in this regard, but the consumer should also have choices, but they ought to be wise about those choices and if they choose to give away personal information, they should know the risks, rewards, consequences, and challenges ahead.

Indeed, I thank you very much, and be sure to pick up a handout on your way out, if you didn't already get one, from the good looking blonde, Sherry, at the door. Thanks again, and let's take a 5-minute break, and then head into the question and answer session, deal?



Source: http://ezinearticles.com/?Data-Mining-and-the-Tough-Personal-Information-Privacy-Sell-Considered&id=4868392

Friday 6 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

Thursday 5 September 2013

Things You Should Know about Data Mining or Data Capturing

The World Wide Web is a portal containing billions of quality information, spanning resources from around the globe. Through the years, the internet has developed into a competitive business environment which offers advertising, promotions, sales and marketing innovations that has rapidly created a following with most websites, and gave birth to online business transactions and unprecedented financial growth.

Data mining comes into the picture in quite an obscure procedure. Most companies utilize data entry level workers to edit or create listings for the items they promote or sell online. Data mining is that early stage prior to the data entry work which utilizes available resources online to gather bits and pieces of information relevant to the business or website they are categorizing.

In a certain point of view, data mining holds a great deal of importance, as the primary keeper of the quality of the items being listed by the data entry personnel as filtered through the stages under data mining and data capturing.

As mentioned earlier, data mining is a very obscure procedure. The reason for my saying this is because of the fact that certain restrictions or policies are enforced by websites or business institutions particularly on the quality of data capturing, which may seem too time-consuming, meticulous and stringent.

These methodologies are but without explanation as well. As only the most qualified resources bearing the most relevant information can be posted online. Many data mining personnel can only produce satisfactory work on the data entry levels, after enhancing the quality of output from the data mining or data capturing stage.

Data mining includes two common strategies. The first one would be a strategy based on manual labor and data checking, with the use of online or local manual tools and scripts to gather the right information. The second would be through the use of web crawlers or robots to perform the task of checking for information on various websites automatically. The second stage offers a faster method for gathering and listing information.

But often-times the procedure spit out very garbled data, often confusing personnel more than helping.

Data mining is a highly exhaustive activity, often expending more effort, time and money than other types of work. Leveling them out, local data mining is a sure fire method to gain rapid listings of information, as collected by the information miners.




Source: http://ezinearticles.com/?Things-You-Should-Know-about-Data-Mining-or-Data-Capturing&id=256125

Tuesday 3 September 2013

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.



Source: http://ezinearticles.com/?Unleash-the-Hidden-Potential-of-Your-Business-Data-With-Data-Mining-and-Extraction-Services&id=4642076

Sunday 1 September 2013

Web Data Extraction Services

Web Data Extraction from Dynamic Pages includes some of the services that may be acquired through outsourcing. It is possible to siphon information from proven websites through the use of Data Scrapping software. The information is applicable in many areas in business. It is possible to get such solutions as data collection, screen scrapping, email extractor and Web Data Mining services among others from companies providing websites such as Scrappingexpert.com.

Data mining is common as far as outsourcing business is concerned. Many companies are outsource data mining services and companies dealing with these services can earn a lot of money, especially in the growing business regarding outsourcing and general internet business. With web data extraction, you will pull data in a structured organized format. The source of the information will even be from an unstructured or semi-structured source.

In addition, it is possible to pull data which has originally been presented in a variety of formats including PDF, HTML, and test among others. The web data extraction service therefore, provides a diversity regarding the source of information. Large scale organizations have used data extraction services where they get large amounts of data on a daily basis. It is possible for you to get high accuracy of information in an efficient manner and it is also affordable.

Web data extraction services are important when it comes to collection of data and web-based information on the internet. Data collection services are very important as far as consumer research is concerned. Research is turning out to be a very vital thing among companies today. There is need for companies to adopt various strategies that will lead to fast means of data extraction, efficient extraction of data, as well as use of organized formats and flexibility.

In addition, people will prefer software that provides flexibility as far as application is concerned. In addition, there is software that can be customized according to the needs of customers, and these will play an important role in fulfilling diverse customer needs. Companies selling the particular software therefore, need to provide such features that provide excellent customer experience.

It is possible for companies to extract emails and other communications from certain sources as far as they are valid email messages. This will be done without incurring any duplicates. You will extract emails and messages from a variety of formats for the web pages, including HTML files, text files and other formats. It is possible to carry these services in a fast reliable and in an optimal output and hence, the software providing such capability is in high demand. It can help businesses and companies quickly search contacts for the people to be sent email messages.

It is also possible to use software to sort large amount of data and extract information, in an activity termed as data mining. This way, the company will realize reduced costs and saving of time and increasing return on investment. In this practice, the company will carry out Meta data extraction, scanning data, and others as well.



Source: http://ezinearticles.com/?Web-Data-Extraction-Services&id=4733722