How Data Scraping and Extraction Services can be used to save time and money.

Data scrape is the process of extracting data from web by using software program from proven website only. Extracted data any one can use for any purposes as per the desires in various industries as the web having every important data of the world. We provide best of the web data extracting software. We have the expertise and one of kind knowledge in web data extraction, image scrapping, screen scrapping, email extract services, data mining, web grabbing.

Who can use Data Scraping Services?

Data scraping and extraction services can be used by any organization, company, or any firm who would like to have a data from particular industry, data of targeted customer, particular company, or anything which is available on net like data of email id, website name, search term or anything which is available on web. Most of time a marketing company like to use data scraping and data extraction services to do marketing for a particular product in certain industry and to reach the targeted customer for example if X company like to contact a restaurant of California city, so our software can extract the data of restaurant of California city and a marketing company can use this data to market their restaurant kind of product. MLM and Network marketing company also use data extraction and data scrapping services to find a new customer by extracting data of certain prospective customer and can contact customer by telephone, sending a postcard, email marketing, and this way they build their huge network and build large group for their own product and company.

We helped many companies to find particular data as per their need for example.

Web Data Extraction

Web pages are built using text-based mark-up languages (HTML and XHTML), and frequently contain a wealth of useful data in text form. However, most web pages are designed for human end-users and not for ease of automated use. Because of this, tool kits that scrape web content were created. A web scraper is an API to extract data from a web site. We help you to create a kind of API which helps you to scrape data as per your need. We provide quality and affordable web Data Extraction application

Data Collection

Normally, data transfer between programs is accomplished using info structures suited for automated processing by computers, not people. Such interchange formats and protocols are typically rigidly structured, well-documented, easily parsed, and keep ambiguity to a minimum. Very often, these transmissions are not human-readable at all. That's why the key element that distinguishes data scraping from regular parsing is that the output being scraped was intended for display to an end-user.

Email Extractor

A tool which helps you to extract the email ids from any reliable sources automatically that is called an email extractor. It basically services the function of collecting business contacts from various web pages, HTML files, text files or any other format without duplicates email ids.

Screen scrapping

Screen scraping referred to the practice of reading text information from a computer display terminal's screen and collecting visual data from a source, instead of parsing data as in web scraping.

Data Mining Services

Data Mining Services is the process of extracting patterns from information. Data mining is becoming an increasingly important tool to transform the data into information. Any format including MS excels, CSV, HTML and many such formats according to your requirements.

Web spider

A Web spider is a computer program that browses the World Wide Web in a methodical, automated manner or in an orderly fashion. Many sites, in particular search engines, use spidering as a means of providing up-to-date data.

Web Grabber

Web grabber is just an other name of the data scraping or data extraction.

Web Bot

Web Bot is software program that is claimed to be able to predict future events by tracking keywords entered on the Internet. Web bot software is the best program to pull out articles, blog, relevant website content and many such website related data.

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Web Data Mining Services Overview

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

Entering of data

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


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

Data changing

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

Managing data service

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

Data extraction and cleansing

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

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Tips to Scrape Data of your E-Commerce Website

It is important to keep a close eye on the statistics your e-commerce site provides to ensure that you are correctly targeting your content to your likely audience, and therefore making every sale that should be available to you. Not only that, but you need to be encouraging your potential and actual customers to engage with you, so that you can work on converting them to a customer for life, as well as utilizing their network to promote your products more widely.

The big problem with traffic statistics is that invariably they do not easily indicate the different types of individuals who are arriving on your site. You cannot necessarily discover from your traffic stats whether that visitor came to buy, browse, bargain hunt, or research. There is no one size fits all for content on an e-commerce site, and it can be difficult to ensure that the information most likely to convert to a sale is easily discoverable by the right audience. After all, each type of user may come looking for slightly different things and act upon the information in different ways.

This is where metrics and measurements come in handy. By profiling the different shoppers and visitors to your website, you can begin to understand the different categories of users your promotional campaigns drive to your websites, and hence target information specifically to those visitors. By encouraging them to sign up to a newsletter, open an account, complete a feedback form or survey, or engage with a live contact person, you can begin to build up a picture of the types of people who visit your e-commerce site.

Why? You need to discover who is visiting your site, what their intentions are, and whether you are delivering precisely that they seek.

If you discover that a link on a particular site always leads to a sale of a discount item, or products that are on sale, or multi-buys, you can assume that the majority of those visitors are bargain hunters. Therefore, you can set up a landing page that specifically caters to those seeking a great price or a bargain, and push all of your lower priced deals to those customers immediately they follow the link from the originating site. There is no point pushing the highest spec products to those who are looking for bargain unless your price is highly competitive.

By looking at which type of visitor your back links and certain Pay Per Click campaigns or keywords drive to the site, you can adapt the content or landing pages to suit. Conversion rates can be measured and tweaks and changes made to landing pages to test those rates and increase them.

If you see that you have return visitors who regularly buy, then it is worth targeting those customers with a newsletter highlighting products they have shown an interest in or previously purchased, offer quarterly (or whatever timescale suits them) coupons, discounts and vouchers to repeat customers, and so on. By adding the option to open an account - this should not be compulsory for a first or one-off purchase - you can track our best customers and look after them.

Another way to motivate your customers is to offer an affiliate program that rewards them for their loyalty and promotion of your products and services. This does not necessarily mean purchasing expensive affiliate administration software, and may just mean assigning a single person within the business to communicate with your affiliates to ensure that the relationship is managed so as to be mutually beneficial.

You may discover that there are a number of customers who regularly put multiple items in their shopping basket before checking out, and then remove some of them. If this is the case, you need to check your pricing and shipping costs, and ensure that they are competitive, as well as clearly indicated at the point of purchase. Additionally, if you find a large number of shoppers dropping out before the sale, you must check the usability and functionality of your e-commerce software for ease of use and errors.

By examining the statistics, and applying a few techniques to gather information and then assess it for patterns, you can easily access the goldmine of information which your visitors leave behind. With carefully tailored calls to action, designed to meet your required results and tested regularly to ensure that you are hitting the right targets with your visitors, you can increase the number of responses and thereby achieve what you require from your eCommerce site.

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Major Characteristics of Data Mining Strategy and Visual Analytics

With all the massive amounts of data we are collecting from the Internet, well, it is just amazing the things we can do with it all. Of course, those concerned about privacy, well, you can understand why organizations like the Electronic Freedom Foundation is often fit to be tied. Still, think of all the good that can become of all this data? Let me explain.

You see, with the right use of visual analytics and various data mining strategies, we will be able to do nearly anything we need too. And, yes, I guess it goes without saying that I have a ton of thoughts on Visual Analytics of the Internet, Mobile Ad Hoc networking, and Social Networks along with some concepts for DARPAs plan for "crowd sourcing" innovation, it makes perfect sense to me, as each participant becomes basically a "neuron" and we use the natural neural network scheme.

What we need is a revolution in data mining visual analytics, so the other day I spent 20-minutes considering this and here are my thoughts. I propose an entirely new concept herein. Okay so let me explain my concept. But first let me briefly describe the bits and pieces of ideas and concepts I borrowed from to come up with this;

  1. There is an only UFO or Sci Fi tale I read, where the alien race said; "There is a whole new world waiting for you if you dare to take it,"
  2. Taking the "it" part of that line and calling "it" = "IT" as in Information Technologies.
  3. Next, combining that "IT" or "It entity" with that old Christian apocalyptic "mark of the beast" and the old computer system in Belgium 30-years ago claiming to be big enough to track every world transaction, also nick-named the beast.
  4. Then combining that concept with V. Bush's concept of "recording a life" or the later "life log theory" from Bell Labs.
  5. Then using the concept of the eRepublic, where government is nothing more than a networked website.
  6. Then considering the thought of Bill Gate's concepts in "the Road Ahead" where the digital nervous system of a corporation was completely and fully integrated.
  7. Combined with SAPs, and Oracles enterprise solutions
  8. Combined with Google's data bases
  9. Combined with the Pangaea Project for kids to collaborate in elementary school around the world and programming the AI computer, using a scheme designed by Carnegie Mellon to crowd source the teaching of an AI system. "eLearning Collaborative Networks like Quorum or Pangaea"
  10. Combined with IBMs newest mind map visualization recently in the news..
  11. Combined with these following thoughts of mine:
  • My Book; "The Future of Truck Technologies," and 3D and 4D Transportation Computer Modeling; Page; 201.
  • My Book; "Holographic Technologies," specifically; Data Visualization Schemes; Page 57 Chapter 5.
  • My Article on 3D and 4D Mind Maps for Tracking and Analyzing.
  • My Article on Mind Maps of the Future and Online style Think Tanks
  • My Article on Stair Step Mentorship for Human Learning in the Future and Never Aging Societies.

Okay now let me explain the premise of my concept for Visual Analytics;

First, forget this whole idea of a 2D mind mapping concept or chart used to show links between terrorist players, cells, assets, acquaintances, etc., the way it is laid out currently - make it 3D, actually make it 4D and 5D where some layers can only be seen by a select few, and let's say a 6D level that can only be accessed by an AI super computer [why; because I don't trust humans, they can't be trusted, i.e. WikiLeak, leaker for instance].

Next ALL the data is stored within in the sphere. But to access the data on the outer side of the sphere, picture Earth's surface, the ball or sphere (with grids like a map of the globe) rolls around on a giant grid paper. When you want to look at a particular event, person, subject, or whatever, a particular point on the sphere's grid touches a corresponding point on the grid paper it rolls on, the grid paper it rolls on can wrap around and morph itself to the sphere or contour itself so the next corresponding piece of information on the surface can be accessed, rolling or spinning.

Picture a selectric typewriter ball on a shaft as a 2D model to consider this, now make it all 3D in your mind, and the paper molds around the sphere as it accesses, or in the case of a selectric typewriter it types. Now the Sphere is hollow inside containing layers, just like the earth, crust, mantel, and core. Information goes deep or across, every piece of information is connected, think about the earliest string theory models for this.

Great thing about my visualization concept is I believe all this math exists, even though in reality string theory is mostly bunk, but the math to get there makes this possible. As the information goes deep, think about the iPad touch screen, or the Microsoft restaurant "menu on a table" concept, or the depictions of Minority Reports, moving of the screens by way of motion gestures, I believe Lockheed also has this concept up and running for air-traffic control systems, prototype versions, perhaps the military is already using it, as it has massive applications for the net centric battle space visualization too.

Okay so, some levels go through a frame-burst scenario taking you into another level, where the data generally stored at the almost infinite number of grid points and cross connected to every other is nothing more than a nucleus with additional data spinning around it. But the user cannot access all that information, without clearances, the AI system has access to all of it, while a sorting system is a series of search features within search features, with non-linked data also. You can't break into it; it's not connected to the users' interface at all, think of the hidden data as electrons unattached around the data. The data is known to exist but cannot be accessed that would be the 5D level, and 6D level no human may get too, but the data exists.

You know that surfer dude in Hawaii that came up with the "Grand Theory of the Universe" why not use his model for our visualization, in spherical form, again, the mathematics for all this already exists.

You see, what I need is a way to find people like me, I want to find these thinkers and innovators to take it all to the next level, and if the visualization is there, we can find; The Good Guys, Bad Guys, and the Future all at once. Why do I want a "Neural Network" visualization system in a sphere? It seems to me that this is how the brain does things, and what we are doing here is creating a Collective Brain, using each individual assigned to an "ever-expanding" unit of data, along a carrier or flow.

Remember when Microsoft Labs came out with that really cool way to travel through the Universe and look at all the celestial bodies along the way, using all the Hubble Pictures collected? It's kind of like that, you travel to the information, discover as you travel and it piques your curiosity as you go triggering your own brain waves, and splashing the users minds with chemical rewards as they go, as they discover more information, expanding their understanding as well, it just seems to me this is how it all works anyway.

Think of that old Sci Fiction concept where the Earth and our solar system are merely an atom of a chemical compound within a cell of the human body, all we can see is all the other compounds around us because everything is so small, thus, we cannot see the whole picture and what appears to be an entire universe would only be a few thousand cells close enough for us to see. And time itself is slow, as the electrons or planets moving around the atom appears to take a year to circle the nucleus instead of 10,000 times a second.

So, combining all these types of thoughts, this is how I envision how the future visualization tools would work.

Now then, using the whole concept of connecting the dots for information or even building an AI search feature scouring the system at speeds of terabytes a second, the AI computer can become the innovator, thanks to the user asking the question, and all the neurons (individual humans) with all their data putting in the information. You just need the best questions, you get instance answers.

Okay so, take this concept one step further; the AI super computer's operation is a "brain wave" and that brain wave is assigned a number, you can have as many brain waves, as the internet has IP addresses, with whatever scheme for that you choose. And your query can search the former queries too. The user's questions are as important as the data itself.

Thus, it helps us find the innovators, the question askers, once we know that, we have the opportunity for unlimited instant knowledge. Data visualization can take us there, and it removes all the fog of uncertainty, and answers most all the questions we could ever hope to ask, and comes up with its own questions as well. Does this make sense?

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How to Handle Scraping Issues Efficiently and Stay Focused and Legal

There is an ongoing debate on how much data can be scraped legally and how to prevent scrapers from accessing and gathering data about people without their knowledge. This and other web scraping issues have been bombarding the data mining world for years now. As an individual data miner or as a company that does it for profit, here are tips on how to handle these kinds of issues and stay focused and legal.

Since web scraping is an essential part of online success in business and research, you can do it with the following points of consideration: be responsible; stay within legal bounds; be ethical; and empathize with online users.

Be Responsible

It is expected of every mature individual to be responsible and accountable for every move he or she makes. This notion can amply be applied in the practice of data mining and every other online activity.

First, it must be understood that the Internet is generally a public domain. Every time you access it and make interactions with other users and sites, you are opening yourself to a wide array of possibilities. Thus, you must be careful with every data you share. Since you are putting yourself in a risky place, you have to be ready to face its consequences. This is not to say that anybody can simply have the freedom to your personal or company’s information. It is simply a reminder that you have to be responsible for your actions and to be able to safeguard your account by following expert advice.

Next, on the part of the scraper, you have to bear in mind that if you can access the information about people and organizations, it does not mean you can sell it and enjoy the profit at the expense of others. One of the best ways to show that you are scraping maturely and responsibly is for you to seek permission and inform the source that you are going to use their data. This may sound difficult and to some extent absurd but it is proper.

Third, selling others’ information is indeed ethically questionable; thus, you have to make your web scraping limited to what is permissible such as: keeping out people’s names; retrieving statistical information only; and by acknowledging the source of information. Many sites that can be accessed publicly such as online news and reports are considered public property but it always pays inform the source that you are using them or citing them for whatever purpose you may decide on.

Stay Within Legal Bounds

As a responsible scraper, you must understand the issues of privacy and confidentiality. You can use collected information for your own benefits but you have to bear in mind that you are not hurting or putting to harm anyone’s life and welfare. You can be the judge as to what specific data can be used for your own purposes and what data should be kept to protect the individuals or organizations you take it from or you are accessing. Beware of online theft; it can put your own reputation and credibility in jeopardy.

If you want to have a long-staying data mining experience, you have to use judgment in your online activities. Be aware of your own rights privileges so that you will not run into trouble and be subjected to existing cyber laws or be totally banned from using or accessing many good and sites.

Be Ethical

Practicing a sense of accountability for your web scraping activities is indeed necessary. Whatever it is that can harm others must be kept out of your system or public revelation. You may use them to predict trends and understand clients’ preferences; but you have to make sure that you are not revealing too much.

Ethics spring from respect of others’ rights and freedom. As earlier stated, whatever you put online are for others to view and enjoy. You lose a great portion of your privacy if you share any personal information online. Therefore, both the Internet user and the data miner must bear in mind that there is a need for mutual respect and a sense of accountability,

Empathize With Online Users

The best test of a good web scraper lies on his or her ability to understand others’ feelings and experience their fears and hurt. This attribute can make you scrape within bounds and still be able to benefit from the data mining activities as best as he or she could. Knowing the possible side effects of your action can improve your chances at getting the right information from the right sources.

Many of you may have felt how it is to be robbed or betrayed. These are usually the feelings of those whose information have been used without their knowledge or those who have inadvertently entered so much information online out of ignorance or sheer trust that they can still keep themselves anonymous.

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Updating your Database will Assure you of Good Quality Data

Merely gathering data through web scraping is not enough. It is actually just one of the many processes one has to undergo in this vast field of data collection. The information must be perpetually updated in order to have it always safe and reliable. Updating your database will assure you of good quality; unadulterated data; and secure recording.

Through the years, the development of online web research has greatly improved and has helped a lot of people and establishments in attaining better database as well as successful businesses and functions. Regular updating of your database can result in: new data; renewed information; and up to date material.

New data

One of the ever changing aspects of the human life these days is the information that is generated everyday and even every minute or every time there is a new input. There seems to always be something new about just anything. The popular social networking, for one, is always presenting something new all the time. Your friends post new photos; shouts; opinion; locations; destinations; and a host of other data such that missing a day or two from opening your account may cause you to miss a lot of information about your favorite sites and people.

Enhancing the quality of your database is one of the results of updating your files. Good thing that some data mining services have a built in way of helping you update your records automatically and regularly. You can then be assured that you have better and improving data as the days and weeks go by. You will also be assured of new and updated information as you continue to use web scraping services.

Renewed information

Not only that your data is new and increasing in value but that it is continually made up to date. Any innovations and additional features in the information you gleaned from different sources are added to your record as you eliminate the obsolete and unnecessary details.

Cleansing your database can also prevent you from information overload. This is an effective way of only retaining what is necessary and what applies to your present and future needs. With the cleaning comes newer versions and updated information. In this way, your business will always be timely and new as you survive and thrive in the very competitive world these days.  The more up to date your data is, the greater are your chances of being pushed to the frontlines and leading in the field you have ventured in.

Up to date material

Moreover, maintaining the new-ness and relevance of your data can also be an effective way of safeguarding your data from any contamination and intrusion. Your passwords, for instance, can be changed regularly so that hackers cannot access and steal your information. This is also a way of protecting your files from virus and any malicious components.

When your data is secure and updated, you can be assured of accurate and sustainable information that will carry you through your business or research venture. Security is one of the main concerns of businesses and entities because anything can just happen in this age of high technology. You must be sure that your files are still intact and pure so that when you need them you can maintain as well as achieve better results and solutions to challenges and problems.

Updating your database is one of the best things that you can do to get the best from web scraping and data keeping. You always have fresh data that is suitable for each new need; clean and undiluted information for accurate solutions to your needs; and secure files that no one can tamper and steal. Since you are in a highly competitive world, there is no place for carelessness and procrastination. If you have decided to join the race, you have to eliminate any unnecessary weights; the same is true in any form of venture that you have decided to undergo these times. You have to make sure you have done your best to be as clean and renewed as

Finally, you must always bear in mind that keeping your files is like staying alert in battles. You have to always be on guard against invaders and spies if you want to maintain your winning status and in order to stay on your ground unwavering and strong. All these may sound impossible and too ambitious; however, data mining service providers never stop improving their services. These experts are your allies as you take risks and stay in the race. Many of today’s successes are greatly helped by the reliable web scrapers whose aim is to provide the best service and who never stop learning and innovating their software’s and techniques so that excellence is not sacrificed. Lastly, in these changing times, only the people who continually update their files are the ones who always get the best data first.

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The Major Online Source of Data Mining and Data Entry

Data entry job involves transcribing a particular type of data into some other form. It can be either online or offline. The input data may include printed documents like Application forms, survey forms, registration forms, handwritten documents etc.

Data entry process is an inevitable part of the job to any organization. One way or other each organization demands data entry. Data entry skills vary depends upon the nature of the job requirement, in some cases data to be entered from a hard copy formats and in some other cases data to be entered directly into a web portal. Online data entry job generally requires the data to be entered in to any online data base.

For a super market, data associate might be required to enter the goods which have sold in a particular day and the new goods received in a particular day to maintain the stock well in order. Also, by doing this the concerned authorities will get an idea about the sale particulars of each commodity as they requires. In another example, an office the account executive might be required to input the day to day expenses in to the online accounting database in order to keep the account well in order.

The aim of the data mining process is to collect the information from reliable online sources as per the requirement of the customer and convert it to a structured format for the further use. The major source of data mining is any of the internet search engine like Google, Yahoo, Bing, AOL, MSN etc. Many search engines such as Google and Bing provide customized results based on the user's activity history. Based on our keyword search, the search engine lists the details of the websites from where we can gather the details as per our requirement.

Collect the data from the online sources such as Company Name, Contact Person, Profile of the Company, Contact Phone Number of Email ID Etc. are doing for the marketing activities. Once the data is gathered from the online sources into a structured format, the marketing authorities will start their marketing promotions by calling or emailing the concerned persons, which may result to create a new customer. So basically data mining is playing a vital role in today's business expansions. By outsourcing the data entry and its related works, you can save the cost that would be incurred in setting up the necessary infrastructure and employee cost.

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Keeping your Online Information Safe and Uncompromised

With the easy access of most users to Internet publication and links, there is no doubt that many other users are wary of the possible intrusion of privacy and property of their websites and the information they attach to these.

With this uncertainty, keeping your data online and safeguarding as well as accessing them can be a serious issue to handle. Web scraping done by suspicious entities can cause damage to your reputation and even your very own system. Although you may have practiced responsible data mining and have been very careful in handling scraped information, still, you cannot fully control how other people or groups may scrape data from you or your other links.

In view of this, how can you secure your data when you are not even sure or aware that it can be accessed by just anybody? Here are practical ways of keeping your online information safe and uncompromised for certain periods of time.

Exercise Caution

Since every action you take can put a mark on online paths, you simply cannot be careless. Hence, do not give valuable information without being certain that you are venturing into a legal and secure site. Although web scraping can be done easily, you have to be sure that what you gather is free from threats of virus and spam as well as that it should be truly beneficial to you.

In addition, because you cannot fully control the way others use your site and the information you put in it, you can still monitor it. There is therefore a need for you to find an effective way of checking who and what goes through your system. You can track online coverage and make necessary changes when necessary. Find a service that makes you find a way of receiving alarms in your mobile when access has been made on your website especially that of suspicious ones.

Update Security Codes Regularly

As usual, keeping a password is one of the most common ways of protecting your data. However, you have to change it every now and for your own safety and convenience. It is always wise to adhere to advice that your password or security code should be different from your personal identification such as relevant dates and names such as that of birth or initials. Hackers can be very clever and really creative so you have to be very watchful.

You can keep a record of the date you have changed your password and be consistent in following that schedule. There is just simply no time for complacency in keeping your valuable information safe because these can be used by others for their own benefits in exchange for large amounts of money; while you may be put in jeopardy for being exposed to your competitors.

Clean Caches Frequently

One of the avenues where you can let the enemy in is through caches and history that has not been removed and cleaned. Like footprints, these can be retraced and can lead back to you and your precious data. Some data mining tools are like spiders that crawl within sites without the knowledge of its owners. Moreover, they can be inconspicuously fast that before other owners can discover it, they have been robbed of precious information.

This act of cleaning may appear a little trivial and can thus be neglected and forgotten; but just imagine how much you will lose in just a few seconds of neglect. There is indeed wisdom in being clean and putting things in order. Just like changing your security codes, you must have a scheduled cleaning of your caches so that you can prevent anybody or anything from accessing your files illegally.

Update Database

Another yet effective means of securing your files is to update your data. You can schedule a regular updating of your data so that any excessive items can be eliminated and any trace of connection to some visited sites that you no longer need can be removed. You just do not know when the enemy can get into your camp, thus, you have to employ security of information whenever possible.

Moreover, there may be some information that you have gathered in the past that has been linked to unsafe sites, so you have to be sure to remove superfluous external links as well as eventually eradicating such old and outdated files. Being ahead of others and being well-informed about recent developments in science and technology as well as business and research can be of great advantage. Why not grab these blessings of the modern times and stay ahead of others?

Being always on the alert mode in your data preservation and storing can cause you less worry of intrusion, theft, and virus. Just like keeping yourself clean can lead to better health, so does your database. When you have kept it continually free from traces of unknown links, you can be on your way to safety and success.

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Web Data Mining: A Systematic Approach to Keyword Based 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 Page Rank. Google uses Page Rank 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.

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Data Mining : A link Between Separate Transactions and Analytical Systems

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

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

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

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

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

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

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Today’s data collection through web scraping is quick and comprehensive

Can you imagine life without the capacity to collect data in the manner we do these days? Today’s data collection through web scraping is quick, comprehensive, and can be effortless. Gone are the days when you have to go to the files, archives, people, and place through great distances and barriers just so that certain valuable information can be gathered.

With the way things are, it seems impossible to go back and use the usual methods of getting information. Data mining has become so fast and even convenient that it appears to be the only and the best way to stay successful in business and in research. As of now, nothing can seem to replace the way web scraping has impacted information procurement and tracking.

Across Physical Boundaries

Only a decade or two ago, one has to exert efforts to literally cross boundaries by traveling in order to get data from libraries, museums, archives, companies, institutions, and people. This effort is not only physically draining but also financially depleting. Moreover, the success rate is not also assured especially when some data may have been lost or passed from one person or location to another.


Today, what you simply need is a computer and an Internet connection and you can reach and verify as well as retrieve the data through electronic means. There are less people involved and less money to spend because you travel not by geographical means but through virtual space. Data mining has crawled all over the world subtly and silently.

Past Restrictions

Few years back, you cannot just get into a library or institution without proper identification and certain adherence to protocol. Entering a certain area can be difficult and data collection is even more difficult because of limited chances of borrowing and copying some contents of books and materials. For example, some historical data are in microfilm form such that you have to view them personally and do some note taking by hand.

These days, most of the information are published or stored in websites so that you can access them freely or you can sign up or subscribe to such websites and you can browse through their data and gather all the necessary information for your company or research work. Some clever researchers can even get through restrictions and security codes set by some websites for their own protection and some kind of intellectual property issues.

Regardless of Time

Time is an important element in gathering information. It is dependent on the kind of material you will need and the relevance of the age or timeliness of that data to you or your clients. Some time ago, the older files can be easily acquired over the newer files because they have been put to record already. However, the newer ones were more difficult to access because they have not been recorded yet.

Today, everything has seemed to have been in print or visual presentation online within seconds of its conception or release. For instance, if you want to know the results of important activities such as sports or board examinations, you will find them easily online. In addition, such information is updated regularly and frequently.

Beyond Imaginations

In the past, we usually marvel at the science fiction movies that portray lives and exploits that uses time machines. During those times, such travels and activities were dismissed as impossible and simply products of the human imagination. However, looking at the way things are in the present cyber world, anything can just happen.

It would not be a wonder if one of these days, someone will come and introduce the time machine. Now, people will no longer respond with unbelief because anything indeed can happen. Whatever a person can think about these days can be put into a reality. The word impossible appears to be nonexistent now because of the way technology has improved and simplified access to information. Because of this, anything can simply happen.


Today’s geniuses are really outwitting the obstacles set by time, distance, people, and imagination. It is unthinkable what will be the next invention by the experts in science and technology. Now that Mars is a potential for human habitation and some individuals have volunteered to live there, data mining as an indispensable act can surely become interplanetary and universe-wide in scope.

On the downside, less and less privacy can be attained and maintained by many individuals and entities. Since there is an easy access to information once they are posted or attached online, then we will lose one of the precious privileges we usually enjoy. Almost if not all of the people who have accessed the Internet or who have allowed their information to be used through electronic means such as emails and social networking can be recorded, accessed and used by others through data mining.

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The science of managing and storing data

One thing about today's forever growing data. It is imperative to keep data up to date and organized on a continuous basis. In today's digital society, companies need to share their information with relevant businesses on a daily basis.

Data is first gathered, inspected, cleaned and validated by a data analyse, then stored in data mining warehouses. The purpose of this data is for companies to make quick decisions with summarized data.

(More details and real time updates to data are available in data bases in contrast.) It is then stored in data warehouses to be extracted on demand by authorized personnel. Data is put into:

  • classes to locate data in predetermined groups
  • clusters grouped according to logical relationships
  • associations to locate data in predetermined groups
  • sequential patterns that anticipate patterns and trends.

What is Data Warehouse?

Data Warehouse leads to a direct increase in quality of analyses as the table structures are simpler in a stable read-only database that combines information from separate systems into one easy-to-access location.

Accessing and inputting data happens at specific times and is accessible to certain authorized individuals. This is pretty much like a library with regular working hours, except that the information is only available for people with library cards.

This enabled a new job called Data Mining. Data Scientist is sought after in the growing need for information interpretation. These new data geeks are in demand. So if you are good with statistics this may be a great field for you.

Wal-Mart allows 3,500 plus suppliers, to access data on their products (via a data warehouse) and perform data analyses.

What Is Data Mining?

Data Mining is a thoroughly long process of sorting and collecting data through massive predictive digitally hidden information and interpreting it into useful information. Mostly used by consumer driven companies Company’s need this for global growth and new innovative product launches.

Today, data mining applications are available on all size systems for mainframe, client/server, and PC platforms. The more data being processed and maintained, the more powerful the system required thus determining the size of the database. A data mining technician is needed to read the data and translate into understandable language to solve and report concerns when they arise. More available training is sought after more and more.

Data engineers are becoming just as important as accountants in today's computerized operations that run on a massive amount of information. These businesses have to use the latest technology to compete and remain successful.

What Is A Data Analyst?

A Data Analyst is someone who uses computer software to analyze large amounts of data which is collected, organized, validated, cleaned and has the ability to translate data to easy to understand English

How to Become a Data Analyst

No Special degree in necessary for becoming a data analyst and enjoying numbers is a plus. There are 3 steps to becoming a data analyst.

  1. Post secondary degree.
  2. Related work experience.
  3. Computer Skills

Data Analyst Salary

A data analyst salary starts about $50,000 upward to $100,000 depends on the type of analyst you are researching, there are multiple levels with multiple disciplines.

What Is A Data Scientist?

A superior, but evolved data analysis that can interpret data in moments and can turns data into products and useful information. Data Scientist is considered a data specialist and strategic art form.

How Do I Become A Data Scientist?

A degree in Information Sciences with a strong business and programming background may get you hired but it is best to have statistic knowledge and some knowledge with the company’s products as well.

Predictive Analytic Training seems to be a great place to start toward gaining experience. However more well trained people will be in demand as the future courses are developed.

Data Scientist Salary

As of 2010 the data mining salary was about $112,000. Self employed Data Scientist can make much more. Data Scientist earns more in the United States.

The science of managing and storing data is not a fad and is here to stay. The way we get into the business is ever evolving and the training will soon be more specific. Data warehousing and data mining jobs are on the rise as well and pay very well. If you have a college degree this may be something you may want to consider. There's nowhere to go but up if you do.

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Efficient data mining techniques to extract data easily

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

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

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

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

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

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

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Relationship Between Quantitative and Qualitative Data

What is Quantitative Data?

Quantitative data is data that can be quantified and expressed as a number. Quantitative data is measured, counted and easily analyzed. For data to be quantitative, it must have a definite scale of measurement, be it Kelvin, nanometers, feet or Farads. Quantitative data and qualitative data can be collected simultaneously, measuring or documenting different attributes of the same products or processes. Qualitative data collection is repeatable. Different people using measuring equipment should get the same or very similar values for the same qualitative variable.

Qualitative data measures or classifies qualities, such as gender, race, citizenship or religion. Quantitative data measures quantifiable values such as age, weight, height or white blood cell count. Qualitative and quantitative data may be collected simultaneously, such as checking off “yes/no” binary questions like “Are you married?” and “Do you have children?” along with someone’s age and time spent at their current residence in a sociological study. Qualitative data collects information that adds depth and reveals deeper trends than quantitative data may reveal. For example, a trend of increasing weight with age is better understood when it is correlated to qualitative data such as marital status, having given birth to children or starting college. In databases, qualitative attributes like gender and notes about someone's health are recorded alongside quantitative data like blood pressure and recorded heart rate.

Analyzing Quantitative Data

Some of the most common statistics are used to analyze quantitative data. The mean or average is found by totaling the quantitative data and dividing by the number of data points. The median is found by arranging all data points in order from smallest to largest and then finding the middle one. Medians identify a middle value without being skewed up or down by extreme values in the data set. For example, a single billionaire in a town will dramatically increase the average net worth in a small town, but his or her influence will hardly affect the median net worth. The range is found by subtracting the largest value and the smallest value. The range is a simple value that indicates the extremes of the data set.

Variance measures variation within a sample relative to the mean or average. Standard deviation measures the dispersion of the data. Standard deviation is found by taking the square root of the variance.

Extrapolation is the process of determining the mathematical equations that tie the quantitative data points together. Equations derived from quantitative data analysis are used to predict future behavior of a system.

Concerns about Collecting Quantitative Data

While qualitative data may be gathered through check sheets or story boards, quantitative data gathering is easily automated. Whether dimensions are captured by automated cameras or digital scales, quantitative data is routinely captured through electronic or computerized means. This simplifies later quantitative data analysis. However, automated data collection does not eliminate all possible concerns about gathering quantitative data.

When collecting quantitative data, the best results occur when data collection is complete. All questions or measurements should be collected in each sample or interview. A second consideration is accuracy. Was the measurement taken correctly, resulting in the actual value? Data collection should be performed using a standard and repeatable methodology. The same time interval or sampling rate must be used throughout the study.

Whether collecting quantitative or qualitative data, it is important to avoid selection bias. In selection bias, the sample is not random and thus biased. For example, allowing those who belong to a specific religious or ethnic group to self select for a study on that group could lead to those who see themselves as good examples of the community to answer sociology studies. The results of the study will generally be better than a random selection of members of the community. Conversely, an academic study on tutoring or remedial curriculum based on parents who choose to join could yield a population whose members are doing unusually poor with more motivated parents than average. The children would have lower scores than the average group, since the children who are doing relatively well in the class probably would not join the study, while parents who are not motivated to improve a child’s performance will not join. The fact that the data is quantitative instead of qualitative does not eliminate the risk of selection bias in the study. Using scanners to grade children’s tests and tabulate the results does not eliminate bias if the student sample itself is biased.

Bar charts can be used to present quantitative data like total spending.

Source: Tamara Wilhite

Presentation of Quantitative Data

Quantitative data is often presented as data points on a graph or chart. Run charts track a single quantitative value over time. Statistical process control charts or SPC charts are line charts that show the value of a quantitative variable over time and relative to acceptable limits or control limits. Box plots depict both averages and ranges. Furthermore, quantitative data can be presented in almost any type of chart.

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Importance of Data Mining Tools in eCommerce Business

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.

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Implementing Business Intelligence in Data Mining Efforts

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.

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How to Deal With eCommerce Data Collection

In piecing together a research design, data collection procedure is one important consideration. Data collection procedures answer the who, when, and how of research proposal or research project. This hub looks to research design expert John Creswell to glean insights into proper data collection procedures and techniques.

Four Steps to Data Collection Research Design

According to Creswell (2009), four steps related to the data collection process include (a) the determination of the purpose of the research; (b) the format e.g. quantitative survey or qualitative interviews; (c) the sample - i.e. who should be included in the study, and the sample size – i.e. how many should be included; and (d) whether the survey should be cross-sectional – i.e. the data collected at one point in time, or longitudinal, wherein data is collected over time as in quantitative studies.

Quantitative Qualitative

A quantitative research design uses a survey questionnaire to poll participants about a certain subject. A qualitative study involves careful observation and or interviews of members of the group under study. Unless the study uses a pre-test post-test design, most quantitative studies are taken at one place and time whereas qualitative studies seem to take place over an extended period of time. It is difficult to gain a sense of a particular society or phenomena through observation at one place and time.

Cross-sectional or Longitudinal

When collecting data in a quantitative study, the researcher must determine if he will collect pass out and collect the data surveys at one place and time or over an extended period of time. A data collected at one place and time is called cross-sectional whereas data collected over an extended period of time is labeled longitudinal.

More Guidelines for Quantitative Studies

Another consideration for data collection in quantitative study is distribution method. This point refers to how the researcher will distribute and collect the survey questionnaires. One method is personal distribution by which the researcher hands or sends a copy of the survey directly to the target participants. A second technique is to place the survey online through SurveyMonkey or some other service and allow people to randomly access the questionnaire according to convenience and interest level.

More General Guidelines for Qualitative Studies

Creswell (2009) also pointed out that in qualitative studies other data collection procedures would include (a) purposefully selecting participants and sites for interviews and observations; (b) how best to record qualitative observations i.e. take field notes; (c) how to conduct interviews i.e. how many interviewees at one time, what kind of questions to ask them; (d) what if any documents should be collected and how best to analyze them; and (e) whether to audio and visual material.

How to Deal with Collected Data

Another consideration when setting up a research design is how one will analyze the data after collecting it. Kerlinger and Lee note that this includes coding and content analysis procedures.

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Data Mining Services are Achieving Competitive Edge in Business

Mining of data in general terms can be elaborated as retrieving useful information or knowledge for further process of analyzing from various perspectives and summarizing in valuable information to be used for increasing revenue, cut cost, to gather competitive information on business or product. And data abstraction finds a great importance in business world as it help business to harness the power of accurate information thus providing competitive edge in business. May business firms and companies have their own warehouse to help them collect, organize and mine information such as transactional data, purchase data etc.

But to have a mining services and warehouse at premises is not affordable and not very cost effective to solution for reliable information solutions. But as if taking out of information is the need for every business now days. Many companies are providing accurate and effective data and web data mining solutions at reasonable price.

Outsourcing information abstraction services are offered at affordable rates and it is available for wide range of data mine solutions:

• taking out business data
• service to gather data sets
• digging information of datasets
• Website data mining
• stock market information
• Statistical information
• Information classification
• Information regression
• Structured data analysis
• Online mining of data to gather product details
• to gather prices
• to gather product specifications
• to gather images

Outsource web mining solutions and data gathering solutions has been effective in terms of cost cutting, increasing productivity at affordable rates. Benefits of data mining services include:

• clear customer, service or product understanding
• less or minimal marketing cost
• exact information on sales, transactions
• detection of beneficial patterns
• minimizing risk and increased ROI
• new market detection
• Understanding clear business problems and goals

Accurate data mining solutions could prove to be an effective way to cut down cost by concentrating on right place.

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Web Scraping and Data Collection for Online Retail Shops (e-commerce)

Web scrapping which is also referred to as web data extraction or web harvesting is of utmost importance in any and every ecommerce shop that strives to succeed.  It is one of the easiest ways to monitor your market and the ecommerce industry in general.  Web scrapping in its simplest form is described as the process of collecting information from the web automatically. A web scrapper is a computer software technique that is used to extract data or information from as many websites as is needed.  This computer software program helps to stimulate people (potential clients) to explore the web by either embedding specific known browsers such as Mozilla and/ or Internet Explorer, or implementing a smaller degree of Hypertext Transfer Protocol (HTTP).

Web scrapers are best used for market research, and are called ants, web spiders, automatic indexers, web robots, bots, and more. They are computer programs used to browse the web in an automated, orderly and methodical manner, called web crawling. Most site engines use web scrapers to provide up-to-date information that will help create copies of all their web pages visited. When these are processed, search engines then proceed to index all the downloaded pages. Indexing by search engines; helps for a faster and easier search, makes gathering of certain types of information easy, and it also helps with automating regular maintenance tasks on an ecommerce shop or website.

Web scrapping is simply web automation, which stimulates human web browsing using software programs. The uses of web scraping in an ecommerce shop are; for web research, price comparisons on the internet,   web data integration, content integration or mashup, detection for website change, data and information monitoring and more. A web scrapping from an exemplary point of view is like a person visiting a website by entering its URL on the web browser and then collects information from that website. In essence,  web scraping does this same job but not by typing in a URL but by crawling (spider-like) using Algorithms which works with only scripting languages such as Python, PHP, Perl and many more.

From a competitive analysis, web scraping is very important for the success of any ecommerce shop/ website because;

It helps you automatically copy and paste thousands of data from as many WebPages as you want.

It enables you scrap data from your target website and export its contents in a variety of different formats such as   Microsoft word, PowerPoint, excel, MySQL  format, rich text format and more.

Web scraping can be used to convert contents that are not well structured into well-formatted contents. It can also be used to extract product descriptions, and online ecommerce shopping data, financial information, email addresses, news contact details and all other information online.

This computer software can also gather information or data from business directories, ecommerce websites, shopping sites, search engines, job portals and other important contents online on its own without manual assistant.

Web scraping which is also referred to as screen scraping functions hand in hand with a concept called data mining.  While web scraping allows you gather information online from a variety of websites, data mining allows you to analyze the information gotten. Data mining is describes as the practice of searching large data stores automatically for patterns. In essence, data mining allows you to learn about the data gotten. It often times is a statistical method based on complex algorithms.  Note that it does not have anything to do with gathering data or knowing how you got the data, it just analyzes information.

Another term used with web scraping, and data mining is data collection.  Data collection as the name implies is described as the process of arranging and collecting data. Data collection was created for obtaining information for record purposes, used for decision-making on vital issues and is used to pass information to other people. In the simplest form, data collection is data gathered to provide information on a specific subject.

In summary; while web scraping is the process of extracting information from targeted websites using software programs, web mining is the process of analyzing data collected, and data collection is the process of preparing and collecting data.

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How Data Mining Might Actually Help Consumers

With so much concern over privacy in the digital world, it’s worth noting how the careful disclosure of consumer data might actually help. This is especially true in the area of personal finance, where the newly minted federal Task Force on Smart Disclosure seems to be digging in.

The White House authorized the task force last summer with the mission of prying loose consumer information and organizing it in a way that helps individuals make smarter money decisions. The big idea here is that more transparency in how people spend and save would create a baseline that helps consumers spot their own weaknesses. It would also help banks and other institutions better understand the needs of their customers. At the policy level, smart disclosure would help raise the nation’s financial literacy, which would leave us at less risk of a repeat economic meltdown.

This is all open for debate, of course. And clearly individuals’ privacy must be respected. But there is no question that smart disclosure of financial data has the potential to push the nation’s financial education effort forward by a quantum leap. How might it work? Here’s a simple example, which Chris Vein, a White House staffer on technology innovation, recounted last month before a Financial Literacy and Education Commission panel:

Officials had recently convinced three utilities in California to disclose detailed energy consumption records, giving 6 million residents easy access to their full history. A friend of Vein’s downloaded her data and was shocked to see how much she was spending. She decided to investigate. “It turns out that her daughter was taking hour-long showers,” Vein said. “Those showers were requiring lots of hot water, and a hot water heater to heat it. They asked their daughter to stop taking long showers. Low and behold, their utility bill dropped precipitously.”

This kind of data mining is helpful on a personal level. But it’s only a small part of what smart disclosure is all about. The real juice is in unlocking consumer data that third parties synthesize on a broad scale and use to create guidelines and tools that help individuals make smart money choices. Smart disclosure might lead to a smart-phone app that helps you compare insurance policies or mortgages at the point of sale, where it is needed most.

(VIDEO: They Know What You Do: Data Mining on the Internet)

We already have apps that read a barcode at the mall and tell you if a cell phone or video game is available for less somewhere else. “If you’re looking at mortgages and sitting down with a broker, why shouldn’t you be able to take a snapshot of a barcode and instantly have access to information and advice from third parties on that product?” asks Sophie Raseman, a task force member.

Government makes a lot of data available. The challenge is in getting private industry, especially banking, to go along. As Raseman noted: on travel sites like and there is a wealth of clear information to help you choose the optimal flight; yet that level of detail does not exist on a financial website like, where you might look for a mortgage or credit card. And good luck trying to find useful information on the terms of a payday loan.

“The ability to understand and control one’s finances is one of the most important life skills,” said Richard Cordray, director of the Consumer Financial Protection Bureau. “It creates a path to economic independence and mobility. I view it as fundamental to responsible citizenship in our system of economic democracy.”

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