Data Recovery: Beginners Tips

Right now you probably in a lot of mental pain, and all you're concerned about is recovering your data as quickly as possible - so we'll refrain from comments on the wisdom of regular back ups. The time for preventative measures has gone - the issue at hand is data recovery.

First - a simple tip could save you a lot of money. Take out your rolodex and get hold of your tech-savvy friends. If you're in luck, they'll offer to help, and if you're really lucky, they might even have some disk recovery software.

If you're out of luck, then get out your wallet or purse out now... because this is going to cost you. Also, be prepared for a lot of time being wasted - data recovery can take a long time.

The first thing to establish is what exactly is wrong with your hard disk:

    Either your computer won't boot up, or
    Your computer boots up OK but you can't see one of your other drives.

Let's see if we can eliminate the worst scenario. Listen closely to your hard drive - is it making any sort of weird noise, such as scratching, scraping, ticking etc?

If so, then your drive is physically damaged and the only hope that you have is to take it to a data recovery service where experts might be able to get your data off for you. These services are expensive and time consuming - so you need to make a judgement call as to the value of data on the disk:

    If it's only your saved game data or downloaded music files you would like back, you're probably better off kicking yourself for not backing up, and accepting the data loss.
    If, on the other hand, it's a book or other type of information product that you've been working on for years, then send it to a data recovery service for an evaluation and quote - it usually costs nothing.


If your hard disk sounds OK, then you stand a decent chance of recovering data yourself.

First you'll need to download some software to help you out.

Unfortunately, the better software utilities are not free, but the good news is that many allow you to try them out to see they can access the data. There are some freeware versions available but generally speaking these are not easy to use - no user interface / little documentation, or they are not very effective.

There's a list of recommended software on our site - http://www.recoverdatafiles.com - compare the different options then download a few of the trial versions.

Your next steps will be based on how your hard drive/s were setup:

    If you only have a single hard drive that has not been partitioned or split into different "logical" drives, you'll probably need to attach the hard drive to another computer that has enough space to store all your data. This can be quite technical so if you don't have the skills please get a computer savvy friend to help out. Another option is to purchase an external USB hard drive case. You can then simply slot the hard drive into the case and plug it into another PC using a USB port.
    If you have a multiple drive setup and your computer boots up fine, then it will merely be a case of getting the downloaded software to read the files and then copy them to another drive - provided you have a drive with enough space on it. If not, you'll need to attach the hard drive to another machine with enough spare capacity.
    The scenario where you have a multiple drive setup, where the problem drive is the one that contains your operating system files is more tricky. Look for a data recovery software package that has a boot disk option available. What this means is that when you start your computer with the boot disk in it, it will automatically run the data recovery program without trying to start windows. You should be able to see your files and then copy them across to another drive.

Hopefully these tips will enable you to get all your important files back.

Once you've had some time to recover, please take a look at the various articles on our website - our goal is to make it one of the best resources on data recovery.

For the past 20 years, Jeff Walters' interest has been in making the most effective use of a business's information assets. He has lead several data-to-information projects : ABC Costing, analytical CRM, datamart /data warehouse development, and Balanced Scorecard.


Source: http://ezinearticles.com/?Data-Recovery:-Beginners-Tips&id=59035

Various Data Mining Techniques

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

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

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

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

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

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

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


Source: http://ezinearticles.com/?Various-Data-Mining-Techniques&id=6985662

How Web Data Extraction Services Will Save Your Time and Money by Automatic Data Collection

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 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 a 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. Datamining 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 a 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 We have worked with many clients for data extracting, data scrapping and data mining they are really happy with our services we provide very quality services and make your work data work very easy and automatic.



Source: http://ezinearticles.com/?How-Web-Data-Extraction-Services-Will-Save-Your-Time-and-Money-by-Automatic-Data-Collection&id=5159023

How Can We Ensure the Accuracy of Data Mining - While Anonymizing the Data?

Okay so, the topic of this question is meaningful and was recently asked in a government publication on Internet Privacy, Smart Phone Personal Data, and Social Online Network Security Features. And indeed, it is a good question, in that we need the bulk raw data for many things such as; planning for IT backbone infrastructure, allotting communication frequencies, tracking flu pandemics, chasing cancer clusters, and for national security, etc, on-and-on, this data is very important.

Still, the question remains; "How Can We Ensure the Accuracy of Data Mining - While Anonymizing the Data?" Well, if you don't collect any data in the first place, you know what you've collected is accurate right? No data collected = No errors! But, that's not exactly what everyone has in mind of course. Now then if you don't have sources for the data points, and if all the data is a anonymized in advance, due to the use of screen names in social networks, then none of the accuracy of any of the data can be taken as truthful.

Okay, but that doesn't mean some of the data isn't correct right? And if you know the percentage of data you cannot trust, you can get better results. How about an example, during the campaign of Barak Obama there were numerous polls in the media, of course, many of the online polls showed a larger percentage, land-slide-like, which never materialized in the actual election; why? Simple, there were folks gaming the system, and because the online crowd, younger group participating was in greater abundance.

Back to the topic; perhaps what's needed is for someone less qualified as a trusted source with their information could be sidelined and identified as a question mark and within or adding to the margin of error. And, if it appears to be fake, a number next to that piece of data, and that identification can then be deleted, when doing the data mining.

Although, perhaps a subsystem could allow for tracing and tracking, but only if it was at the national security level, which could take the information all the way down to the individual ISP and actual user identification. And if data was found to be false, it could merely be red flagged, as unreliable.

The reality is you can't trust sources online, or any of the information that you see online, just like you cannot trust word-for-word the information in the newspapers, or the fact that 95% of all intelligence gathered is junk, the trick is to sift through and find the 5% that is reality based, and realize that even the misinformation, often has clues.

Thus, if the questionable data is flagged prior to anonymizing the data, then you can increase your margin for error without ever having the actual identification of any one-piece of data in the whole bulk of the database or data mine. Margins for error are often cut short, to purport better accuracy, usually to the detriment of the information or the conclusions, solutions, or decisions made from that data.

And then there is the fudge factor, when you are collecting data to prove yourself right? Okay, let's talk about that shall we? You really can't trust data as unbiased if the dissemination, collection, processing, and accounting was done by a human being. Likewise, we also know we cannot trust government data, or projections.

Consider if you will the problems with trusting the OMB numbers and economic data on the financial bill, or the cost of the ObamaCare healthcare bill. Also other economic data has been known to be false, and even the bank stress tests in China, the EU, and the United States is questionable. For instance consumer and investor confidence is very important therefore false data is often put out, or real data is manipulated before it's put on the public. Hey, I am not an anti-government guy, and I realize we need the bureaucracy for some things, but I am wise enough to realize that humans run the government, and there is a lot of power involved, humans like to retain and get more of that power. We can expect that.

And we can expect that folks purporting information under fake screen names, pen names to also be less-than-trustworthy, that's all I am saying here. Look, it's not just the government, corporations do it too as they attempt to put a good spin on their quarterly earnings, balance sheet, move assets around, or give forward looking projections.

Even when we look at the data from the FED's Beige Sheet we could say that most all of that is hearsay, because generally the FED Governors of the various districts do not indicate exactly which of their clients, customers, or friends in industry gave them which pieces of information. Thus we don't know what we can trust, and we thus must assume we can't trust any of it, unless we can identify the source prior to its inclusion in the research, report, or mined data query.

This is nothing new, it's the same for all information, whether we read it in the newspaper or our intelligence industry learns of new details. Check sources and if we don't check the sources in advance, the correct thing to do is to increase the probability that the information is indeed incorrect, and/or the margin for error at some point ends up going hyperbolic on you, thus, you need to throw the whole thing out, but then I ask why collect it in the first place.

Ah hell, this is all just philosophy on the accuracy of data mining. Grab yourself a cup of coffee, think about it and email your comments and questions.


Source: http://ezinearticles.com/?How-Can-We-Ensure-the-Accuracy-of-Data-Mining---While-Anonymizing-the-Data?&id=4868548

Limitations and Challenges in Effective Web Data Mining

Web data mining and data collection is critical process for many business and market research firms today. Conventional Web data mining techniques involve search engines like Google, Yahoo, AOL, etc and keyword, directory and topic-based searches. Since the Web's existing structure cannot provide high-quality, definite and intelligent information, systematic web data mining may help you get desired business intelligence and relevant data.

Factors that affect the effectiveness of keyword-based searches include:
• Use of general or broad keywords on search engines result in millions of web pages, many of which are totally irrelevant.
• Similar or multi-variant keyword semantics my return ambiguous results. For an instant word panther could be an animal, sports accessory or movie name.
• It is quite possible that you may miss many highly relevant web pages that do not directly include the searched keyword.

The most important factor that prohibits deep web access is the effectiveness of search engine crawlers. Modern search engine crawlers or bot can not access the entire web due to bandwidth limitations. There are thousands of internet databases that can offer high-quality, editor scanned and well-maintained information, but are not accessed by the crawlers.

Almost all search engines have limited options for keyword query combination. For example Google and Yahoo provide option like phrase match or exact match to limit search results. It demands for more efforts and time to get most relevant information. Since human behavior and choices change over time, a web page needs to be updated more frequently to reflect these trends. Also, there is limited space for multi-dimensional web data mining since existing information search rely heavily on keyword-based indices, not the real data.

Above mentioned limitations and challenges have resulted in a quest for efficiently and effectively discover and use Web resources. Send us any of your queries regarding Web Data mining processes to explore the topic in more detail.



Source: http://ezinearticles.com/?Limitations-and-Challenges-in-Effective-Web-Data-Mining&id=5012994

What You Should Know About Data Mining

Often called data or knowledge discovery, data mining is the process of analyzing data from various perspectives and summarizing it into useful information to help beef up revenue or cut costs. Data mining software is among the many analytical tools used to analyze data. It allows categorizing of data and shows a summary of the relationships identified. From a technical perspective, it is finding patterns or correlations among fields in large relational databases. Find out how data mining works and its innovations, what technological infrastructures are needed, and what tools like phone number validation can do.

Data mining may be a relatively new term, but it uses old technology. For instance, companies have made use of computers to sift through supermarket scanner data - volumes of them - and analyze years' worth of market research. These kinds of analyses help define the frequency of customer shopping, how many items are usually bought, and other information that will help the establishment increase revenue. These days, however, what makes this easy and more cost-effective are disk storage, statistical software, and computer processing power.

Data mining is mainly used by companies who want to maintain a strong customer focus, whether they're engaged in retail, finance, marketing, or communications. It enables companies to determine the different relationships among varying factors, including staffing, pricing, product positioning, market competition, and social demographics.

Data mining software, for example, vary in types: statistical, machine learning, and neural networks. It seeks any of the four types of relationships: classes (stored data is used for locating data in predetermined groups), clusters (data are grouped according to logical relationships or consumer preferences), associations (data is mined to identify associations), and sequential patterns (data is mined to estimate behavioral trends and patterns). There are different levels of analysis, including artificial neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction, and data visualization.

In today's world, data mining applications are available on all size systems from client/server, mainframe, and PC platforms. When it comes to enterprise-wide applications, the size usually ranges from 10 gigabytes to more than 11 terabytes. The two important technological drivers are the size of the database and query complexity. A more powerful system is required with more data being processed and maintained, and with more complex and greater queries.

Programmable XML web services like phone number validation will assist your company in improving the quality of your data needed for data mining. Used to validate phone numbers, a phone number validation service allows you to improve the quality of your contact database by eliminating invalid telephone numbers at the point of entry. Upon verification, phone number and other customer information can work wonders for your business and its constant improvement.



Source: http://ezinearticles.com/?What-You-Should-Know-About-Data-Mining&id=6916646

Collecting Data With Web Scrapers

There is a large amount of data available only through websites. However, as many people have found out, trying to copy data into a usable database or spreadsheet directly out of a website can be a tiring process. Data entry from internet sources can quickly become cost prohibitive as the required hours add up. Clearly, an automated method for collating information from HTML-based sites can offer huge management cost savings.

Web scrapers are programs that are able to aggregate information from the internet. They are capable of navigating the web, assessing the contents of a site, and then pulling data points and placing them into a structured, working database or spreadsheet. Many companies and services will use programs to web scrape, such as comparing prices, performing online research, or tracking changes to online content.

Let's take a look at how web scrapers can aid data collection and management for a variety of purposes.

Improving On Manual Entry Methods

Using a computer's copy and paste function or simply typing text from a site is extremely inefficient and costly. Web scrapers are able to navigate through a series of websites, make decisions on what is important data, and then copy the info into a structured database, spreadsheet, or other program. Software packages include the ability to record macros by having a user perform a routine once and then have the computer remember and automate those actions. Every user can effectively act as their own programmer to expand the capabilities to process websites. These applications can also interface with databases in order to automatically manage information as it is pulled from a website.

Aggregating Information

There are a number of instances where material stored in websites can be manipulated and stored. For example, a clothing company that is looking to bring their line of apparel to retailers can go online for the contact information of retailers in their area and then present that information to sales personnel to generate leads. Many businesses can perform market research on prices and product availability by analyzing online catalogues.

Data Management

Managing figures and numbers is best done through spreadsheets and databases; however, information on a website formatted with HTML is not readily accessible for such purposes. While websites are excellent for displaying facts and figures, they fall short when they need to be analyzed, sorted, or otherwise manipulated. Ultimately, web scrapers are able to take the output that is intended for display to a person and change it to numbers that can be used by a computer. Furthermore, by automating this process with software applications and macros, entry costs are severely reduced.

This type of data management is also effective at merging different information sources. If a company were to purchase research or statistical information, it could be scraped in order to format the information into a database. This is also highly effective at taking a legacy system's contents and incorporating them into today's systems.

Overall, a web scraper is a cost effective user tool for data manipulation and management.


Source: http://ezinearticles.com/?Collecting-Data-With-Web-Scrapers&id=4223877

Enjoy Valuable Advantages of Finding Professional Online Data Entry Services

Outsourcing is eyed as a cost-effective means to make the business cycle run. The market consists of a lot of heartened buyers who have enjoyed the fruits of outsourcing by compensating a trivial sum to online data entry service providers. They have felt that the sum they shelled out to these services is quite insignificant when compared to the work they got completed by doing so. Of late, its effect among corporate people is so huge that even those who did not prefer to outsource their projects have embraced this practice realizing quite a few of the several advantages that it has in store. Online Data Entry Services is subcontracted to a lot of individuals and other smaller business units that take such projects as their prime source of occupation.

Many services are distributed to companies who approach these online data entry service providers. Some of the commonly used services are web research, mortgage research, product entry and lastly data mining and extraction services. Adept professionals are at your service in these service providers as those who run such units strongly believe in deploying a team of skilled professionals to help clients realize results as quick as possible. Moreover, the systems that are up for utilization in these units are technically advanced both in terms of utility and security hence you need not fear for having outsourced some crucial data sheets belonging to your company. These providers value your information as how they treasure you association and hence you need not actually care a lot about the confidentiality of your information.

Business firms can look forward to receiving high-class data entry from the hands of online data entry services that undertake such projects. Some of the below-mentioned points are a short listing of what interests business in subcontracting the work to professionals.

    Keying in the data happens to be the first phase at the end of which the companies get understandable information to make strategic decisions with. What appeared as raw data represented by mere numbers some time ago is a pointer or a guide, at present, to accelerate business progress.
    Systems being used for such processes offer complete protection to the information.
    As chances of obtaining high quality information rises, the company's business executive is expected to arrive at excellent decisions that reflect on the company's better performance in future.
    Turnaround time is considerably shortened.
    Cost-effective approach does hold a lot of substance since it considerably decreases the operational overheads related to data entry services within the business wing of the company itself.

Saving money and time holds a unique advantage and outsourcing of such online data entry services proffers these businesses this distinctive edge. Thriving companies intend to focus on their core operations instead of delving into such non-core activities, which do not weigh as good as other essential industrial operations that they need to look after. Why should one take and put these chores on themselves when some professionals who are capable of delivering effective results can be picked from the outsourcing market.


Source: http://ezinearticles.com/?Enjoy-Valuable-Advantages-of-Finding-Professional-Online-Data-Entry-Services&id=4680177

Data Recovery - Hard Drive Data Recovery Services After Computer Crash

Computer crash is something which becomes more likely as your computer ages with time. A computer has hard drive as the data storage unit, which is an electromechanical part, and liable to fail at some point of time. With a few precautions, you may delay its failure, you can not avoid it completely. But with a regular backup, it is possible for a user to avoid data loss that generally accompanies computer crash. However, if a user has not maintained backup, or the backup is not updated, then he has little choice but to opt for hard drive data recovery services.

A drive may crash owing to physical or logical damages. It is easy to prevent crashing of this highly powerful electromechanical device for a long time, by following simple measures. Some of them include:

Prevent overheating of your system. Your system is safe in a cool and dry environment. Heating may cause the circuit board, commonly known as PCB, to get overheated. This board controls the working and can get damaged due to corrosion or power surges.

Make sure your hard drive doesn't fall, or get bumped. In case the impact of fall or bump leads to head crash, then all your data becomes completely inaccessible.

Defragment your drives frequently to prevent data storage in bad sectors and minimize chances for later problems.

Run a good registry cleaner to ensure proper working of your disk drive.

Keep a good internet security suite with antivirus, firewall, and real-time scanning features. As much as possible, buy this from a reliable provider.

Keep your operating system updated with recommended service packs, and updates to ensure it runs properly. Even they help prevent hard drive crash.

Keep power backup, and ensure you don't turn off your computer or running software abruptly. Always use proper procedure for exiting from any application (including operating system). This ensures that the application completes all its procedures, and saves everything properly. It helps increase life of the hard drive as well.

However, when you have encountered a crash, then a backup proves handy in recovering data, and in working normally once again. In case the backup is absent, it is still possible to perform data recovery.

Stellar Informations Systems Ltd., an ISO 9001:2000 certified company is a leading provider of data recovery services. Using high-end proprietary tools, and extensive experience, the company has carved a niche for itself in the data recovery arena. In case a hard drive needs to opened, the company has well-equipped Class 100 Clean Rooms, where invasive recovery procedures can be applied to extract data from the drive.



Source: http://ezinearticles.com/?Data-Recovery---Hard-Drive-Data-Recovery-Services-After-Computer-Crash&id=4810352

Using Charts For Effective Data Mining

The modern world is one where data is gathered voraciously. Modern computers with all their advanced hardware and software are bringing all of this data to our fingertips. In fact one survey says that the amount of data gathered is doubled every year. That is quite some data to understand and analyze. And this means a lot of time, effort and money. That is where advancements in the field of Data Mining have proven to be so useful.

Data mining is basically a process of identifying underlying patters and relationships among sets of data that are not apparent at first glance. It is a method by which large and unorganized amounts of data are analyzed to find underlying connections which might give the analyzer useful insight into the data being analyzed.

It's uses are varied. In marketing it can be used to reach a product to a particular customer. For example, suppose a supermarket while mining through their records notices customers preferring to buy a particular brand of a particular product. The supermarket can then promote that product even further by giving discounts, promotional offers etc. related to that product. A medical researcher analyzing D.N.A strands can and will have to use data mining to find relationships existing among the strands. Apart from bio-informatics, data mining has found applications in several other fields like genetics, pure medicine, engineering, even education.

The Internet is also a domain where mining is used extensively. The world wide web is a minefield of information. This information needs to be sorted, grouped and analyzed. Data Mining is used extensively here. For example one of the most important aspects of the net is search. Everyday several million people search for information over the world wide web. If each search query is to be stored then extensively large amounts of data will be generated. Mining can then be used to analyze all of this data and help return better and more direct search results which lead to better usability of the Internet.

Data mining requires advanced techniques to implement. Statistical models, mathematical algorithms or the more modern machine learning methods may be used to sift through tons and tons of data in order to make sense of it all.

Foremost among these is the method of charting. Here data is plotted in the form of charts and graphs. Data visualization, as it is often referred to is a tried and tested technique of data mining. If visually depicted, data easily reveals relationships that would otherwise be hidden. Bar charts, pie charts, line charts, scatter plots, bubble charts etc. provide simple, easy techniques for data mining.

Thus a clear simple truth emerges. In today's world of heavy load data, mining it is necessary. And charts and graphs are one of the surest methods of doing this. And if current trends are anything to go by the importance of data mining cannot be undermined in any way in the near future.



Source: http://ezinearticles.com/?Using-Charts-For-Effective-Data-Mining&id=2644996

Web Scraping - Data Collection or Illegal Activity?

Web Scraping Defined



We've all heard the term "web scraping" but what is this thing and why should we really care about it?  Web scraping refers to an application that is programmed to simulate human web surfing by accessing websites on behalf of its "user" and collecting large amounts of data that would typically be difficult for the end user to access.  Web scrapers process the unstructured or semi-structured data pages of targeted websites and convert the data into a structured format.  Once the data is in a structured format, the user can extract or manipulate the data with ease.  Web scraping is very similar to web indexing (used by most search engines), but the end motivation is typically much different.  Whereas web indexing is used to help make search engines more efficient, web scraping is typically used for different reasons like change detection, market research, data monitoring, and in some cases, theft.


Why Web Scrape?



There are lots of reasons people (or companies) want to scrape websites, and there are tons of web scraping applications available today.  A quick Internet search will yield numerous web scraping tools written in just about any programming language you prefer.  In today's information-hungry environment, individuals and companies alike are willing to go to great lengths to gather information about all sorts of topics.  Imagine a company that would really like to gather some market research on one of their leading competitors...might they be tempted to invoke a web scraper that gathers all the information for them?  Or, what if someone wanted to find a vulnerable site that allowed otherwise not-so-free downloads?  Or, maybe a less than honest person might want to find a list of account numbers on a site that failed to properly secure them.  The list goes on and on.

I should mention that web scraping is not always a bad thing.  Some websites allow web scraping, but many do not.  It's important to know what a website allows and prohibits before you scrape it.


The Problem With Web Scraping



Web scraping rides a fine line between collecting information and stealing information.  Most websites have a copyright disclosure statement that legally protects their website information.  It's up to the reader/user/scraper to read these disclosure statements and follow along legally and ethically.  In fact, the F5.com website presents the following copyright disclosure:  "All content included on this site, such as text, graphics, logos, button icons, images, audio clips, and software, including the compilation thereof (meaning the collection, arrangement, and assembly), is the property of F5 Networks, Inc., or its content and software suppliers, except as may be stated otherwise, and is protected by U.S. and international copyright laws."  It goes on to say, "We reserve the right to make changes to our site and these disclaimers, terms, and conditions at any time."

So, scraper beware!  There have been many court cases where web scraping turned into felony offenses.  One case involved an online activist who scraped the MIT website and ultimately downloaded millions of academic articles.  This guy is now free on bond, but faces dozens of years in prison and $1 million if convicted.  Another case involves a real estate company who illegally scraped listings and photos from a competitor in an attempt to gain a lead in the market.  Then, there's the case of a regional software company that was convicted of illegally scraping a major database company's websites in order to gain a competitive edge.  The software company had to pay a $20 million fine and the guilty scraper is serving three years probation.  Finally, there's the case of a medical website that hosted sensitive patient information.  In this case, several patients had posted personal drug listings and other private information on closed forums located on the medical website.  The website was scraped by a media-research firm, and all this information was suddenly public.

While many illegal web scrapers have been caught by the authorities, many more have never been caught and still run loose on websites around the world.  As you can see, it's increasingly important to guard against this activity.  After all, the information on your website belongs to you, and you don't want anyone else taking it without your permission.


The Good News



As we've noted, web scraping is a real problem for many companies today.  The good news is that F5 has web scraping protection built into the Application Security Manager (ASM) of its BIG-IP product family.  As you can see in the screenshot below, the ASM provides web scraping protection against bots, session opening anomalies, session transaction anomalies, and IP address whitelisting.

The bot detection works with clients that accept cookies and process JavaScript.  It counts the client's page consumption speed and declares a client as a bot if a certain number of page changes happen within a given time interval.  The session opening anomaly spots web scrapers that do not accept cookies or process JavaScript.  It counts the number of sessions opened during a given time interval and declares the client as a scraper if the maximum threshold is exceeded.  The session transaction anomaly detects valid sessions that visit the site much more than other clients.  This defense is looking at a bigger picture and it blocks sessions that exceed a calculated baseline number that is derived from a current session table.  The IP address whitelist allows known friendly bots and crawlers (i.e. Google, Bing, Yahoo, Ask, etc), and this list can be populated as needed to fit the needs of your organization.

I won't go into all the details here because I'll have some future articles that dive into the details of how the ASM protects against these types of web scraping capabilities.  But, suffice it to say, ASM does a great job of protecting your website against the problem of web scraping.

I'm sure as you studied the screenshot above you also noticed lots of other protection capabilities the ASM provides...brute force attack prevention, customized attack signatures, Denial of Service protection, etc.  You might be wondering how it does all that stuff as well.  Give us a little feedback on the topics you would like to see, and we'll start posting some targeted tech tips for you!

Thanks for reading this introductory web scraping article...and, be sure to come back for the deeper look into how the ASM is configured to handle this problem. For more information, check out this video from Peter Silva where he discusses ASM botnet and web scraping defense.


Source: https://devcentral.f5.com/tech-tips/articles/web-scraping-data-collection-or-illegal-activity#.UbWEetiWbDc

Data Mining Explained

Overview
Data mining is the crucial process of extracting implicit and possibly useful information from data. It uses analytical and visualization techniques to explore and present information in a format which is easily understandable by humans.

Data mining is widely used in a variety of profiling practices, such as fraud detection, marketing research, surveys and scientific discovery.

In this article I will briefly explain some of the fundamentals and its applications in the real world.

Herein I will not discuss related processes of any sorts, including Data Extraction and Data Structuring.

The Effort
Data Mining has found its application in various fields such as financial institutions, health-care & bio-informatics, business intelligence, social networks data research and many more.

Businesses use it to understand consumer behavior, analyze buying patterns of clients and expand its marketing efforts. Banks and financial institutions use it to detect credit card frauds by recognizing the patterns involved in fake transactions.

The Knack
There is definitely a knack to Data Mining, as there is with any other field of web research activities. That is why it is referred as a craft rather than a science. A craft is the skilled practicing of an occupation.

One point I would like to make here is that data mining solutions offers an analytical perspective into the performance of a company depending on the historical data but one need to consider unknown external events and deceitful activities. On the flip side it is more critical especially for Regulatory bodies to forecast such activities in advance and take necessary measures to prevent such events in future.

In Closing
There are many important niches of Web Data Research that this article has not covered. But I hope that this article will provide you a stage to drill down further into this subject, if you want to do so!

Should you have any queries, please feel free to mail me. I would be pleased to answer each of your queries in detail.


Source: http://ezinearticles.com/?Data-Mining-Explained&id=4341782