True Data Recovery Horror Stories

When you lose data, you would want to recover it as quickly as possible. Our financial constraints inevitably play a major part in our decisions, and balancing the two factors makes for a difficult decision making process.

However, if you bungle in your choice of data recovery centre, the results can be deadly. Data which was once recoverable can be lost forever, and literally be ground to dust. And if the data is extremely vital, the consequences can be extremely detrimental.

From recoverable to unrecoverable

A customer had a crashed hard disk from his Apple Computer. He sent in the hard disk to a service provider in a well known electronics centre in Singapore. He was then made to believe that the vendor was one of the authorized Apple Service Centre. He was then quoted around S$1500 and also being promised that he would get back the data in 3 day's time.

On the day he went to collect the data, he was told there and then that the data was "suddenly" not recoverable. As soon as the anxious customer asked for more details of the job, he was told that the disk was serviced by an expert and such professionalism should not be doubted. The vendor further told the customer that the laboratory report was only for internal usage and would not be disclosed, not even the name of the "data recovery expert".

The customer then sent the disk to us. Upon evaluation, it immediately confirmed that the disk was serviced in some "carpeted" office as we saw traces of minute carpet fibres on disk platter, not to mention the dust contaminants. The disk read-write head crashed badly and damaged the platter completely. The head crash might have happened before the service or could have been caused by the contamination of data platter. As far as we could see, such work quality is unacceptable. We had to relate the sad findings to the customer.

We were equally puzzled as the Apple Service Centres will normally direct the customers to us for recovery job. We then contacted the Manager in Apple Service Centre and were surprised to learn that there was no authorized Apple Care Centre around that area.

In this case, a hard disk crash had caused the read/write head of the hard disk to crash onto the platter. It scrapes the magnetic material on the platter (which is where your data is written to by the way) off and takes your data along with it. To know more read this article about hard disk crash, which details the occurrences during a hard disk crash)

Data security worries

The cheap alternative is always enticing. However there are consequences which can jeopardise not only the recovery of your data, but also the privacy and confidentiality of your data. And as a long time data recovery service provider, we have seen quite a number of cases which demonstrates the dangers of sending to unscrupulous 'data recovery' companies.

A customer sent in a crashed hard disk to a computer vendor for recovery. However, he was then told that the data was unrecoverable. Urgently in need of the data, the customer then retrieved the disk from the vendor and sent to us.

We finally rescued all data from the damaged disk. We told the good news to the customer who then rushed to our office to review the data. However, upon further checking, the customer realized that all the data recovered was not his. In fact belonged to some one else! The vendor had returned the wrong disk to the customer probably due to poor logistic control. The original damaged disk is now long gone.

The furious customer cannot do anything. Data confidentiality is an issue as not only has he almost certainly lost his data for good, there is a high chance that someone else posses his disk and can recover his data on it.

Hopefully you can understand the importance of choosing a proper data recovery service provider. The wrong choice can lead to disaster as it can affect not only the recoverability of the data but also can lead you to losing data to unwanted hands.

Suhaimi Baruddin is currently employed as a writer, designer,researcher and data recovery engineer at Adroit Data Recovery Centre's laboratory, which is located in Singapore's Science Hub.


Source: http://ezinearticles.com/?True-Data-Recovery-Horror-Stories&id=905728

Data Mining

Data mining is the retrieving of hidden information from data using algorithms. Data mining helps to extract useful information from great masses of data, which can be used for making practical interpretations for business decision-making. It is basically a technical and mathematical process that involves the use of software and specially designed programs. Data mining is thus also known as Knowledge Discovery in Databases (KDD) since it involves searching for implicit information in large databases. The main kinds of data mining software are: clustering and segmentation software, statistical analysis software, text analysis, mining and information retrieval software and visualization software.

Data mining is gaining a lot of importance because of its vast applicability. It is being used increasingly in business applications for understanding and then predicting valuable information, like customer buying behavior and buying trends, profiles of customers, industry analysis, etc. It is basically an extension of some statistical methods like regression. However, the use of some advanced technologies makes it a decision making tool as well. Some advanced data mining tools can perform database integration, automated model scoring, exporting models to other applications, business templates, incorporating financial information, computing target columns, and more.

Some of the main applications of data mining are in direct marketing, e-commerce, customer relationship management, healthcare, the oil and gas industry, scientific tests, genetics, telecommunications, financial services and utilities. The different kinds of data are: text mining, web mining, social networks data mining, relational databases, pictorial data mining, audio data mining and video data mining.

Some of the most popular data mining tools are: decision trees, information gain, probability, probability density functions, Gaussians, maximum likelihood estimation, Gaussian Baves classification, cross-validation, neural networks, instance-based learning /case-based/ memory-based/non-parametric, regression algorithms, Bayesian networks, Gaussian mixture models, K-Means and hierarchical clustering, Markov models, support vector machines, game tree search and alpha-beta search algorithms, game theory, artificial intelligence, A-star heuristic search, HillClimbing, simulated annealing and genetic algorithms.

Some popular data mining software includes: Connexor Machines, Copernic Summarizer, Corpora, DocMINER, DolphinSearch, dtSearch, DS Dataset, Enkata, Entrieva, Files Search Assistant, FreeText Software Technologies, Intellexer, Insightful InFact, Inxight, ISYS:desktop, Klarity (part of Intology tools), Leximancer, Lextek Onix Toolkit, Lextek Profiling Engine, Megaputer Text Analyst, Monarch, Recommind MindServer, SAS Text Miner, SPSS LexiQuest, SPSS Text Mining for Clementine, Temis-Group, TeSSI®, Textalyser, TextPipe Pro, TextQuest, Readware, Quenza, VantagePoint, VisualText(TM), by TextAI, Wordstat. There is also free software and shareware such as INTEXT, S-EM (Spy-EM), and Vivisimo/Clusty.


Source: http://ezinearticles.com/?Data-Mining&id=196652

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

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

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

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

Let me explain above steps in detail.

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

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

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

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

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


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Data Mining Is Useful for Business Application and Market Research Services

One day of data mining is an important tool in a market for modern business and market research to transform data into an information system advantage. Most companies in India that offers a complete solution and services for these services. The extraction or to provide companies with important information for analysis and research.

These services are primarily today by companies because the firm body search of all trade associations, retail, financial or market, the institute and the government needs a large amount of information for their development of market research. This service allows you to receive all types of information when needed. With this method, you simply remove your name and information filter.

This service is of great importance, because their applications to help businesses understand that it can perform actions and consumer buying trends and industry analysis, etc. There are business applications use these services:
1) Research Services
2) consumption behavior
3) E-commerce
4) Direct marketing
5) financial services and
6) customer relationship management, etc.

Benefits of Data mining services in Business

• Understand the customer need for better decision
• Generate more business
• Target the Relevant Market.
• Risk free outsourcing experience
• Provide data access to business analysts
• Help to minimize risk and improve ROI.
• Improve profitability by detect unusual pattern in sales, claims, transactions
• Major decrease in Direct Marketing expenses

Understanding the customer's need for a better fit to generate more business target market.To provide risk-free outsourcing experience data access for business analysts to minimize risk and improve return on investment.

The use of these services in the area to help ensure that the data more relevant to business applications. The different types of text mining such as mining, web mining, relational databases, data mining, graphics, audio and video industry, which all used in enterprise applications.


Source: http://ezinearticles.com/?Data-Mining-Is-Useful-for-Business-Application-and-Market-Research-Services&id=5123878

Data Mining's Importance in Today's Corporate Industry

A large amount of information is collected normally in business, government departments and research & development organizations. They are typically stored in large information warehouses or bases. For data mining tasks suitable data has to be extracted, linked, cleaned and integrated with external sources. In other words, it is the retrieval of useful information from large masses of information, which is also presented in an analyzed form for specific decision-making.

Data mining is the automated analysis of large information sets to find patterns and trends that might otherwise go undiscovered. It is largely used in several applications such as understanding consumer research marketing, product analysis, demand and supply analysis, telecommunications and so on. Data Mining is based on mathematical algorithm and analytical skills to drive the desired results from the huge database collection.

It can be technically defined as the automated mining of hidden information from large databases for predictive analysis. Web mining requires the use of mathematical algorithms and statistical techniques integrated with software tools.

Data mining includes a number of different technical approaches, such as:

    Clustering
    Data Summarization
    Learning Classification Rules
    Finding Dependency Networks
    Analyzing Changes
    Detecting Anomalies

The software enables users to analyze large databases to provide solutions to business decision problems. Data mining is a technology and not a business solution like statistics. Thus the data mining software provides an idea about the customers that would be intrigued by the new product.

It is available in various forms like text, web, audio & video data mining, pictorial data mining, relational databases, and social networks. Data mining is thus also known as Knowledge Discovery in Databases since it involves searching for implicit information in large databases. The main kinds of data mining software are: clustering and segmentation software, statistical analysis software, text analysis, mining and information retrieval software and visualization software.

Data Mining therefore has arrived on the scene at the very appropriate time, helping these enterprises to achieve a number of complex tasks that would have taken up ages but for the advent of this marvelous new technology.


Source: http://ezinearticles.com/?Data-Minings-Importance-in-Todays-Corporate-Industry&id=2057401

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 Your Online Information is Stolen - The Art of Web Scraping and Data Harvesting

Web scraping, also known as web/internet harvesting involves the use of a computer program which is able to extract data from another program's display output. The main difference between standard parsing and web scraping is that in it, the output being scraped is meant for display to its human viewers instead of simply input to another program.

Therefore, it isn't generally document or structured for practical parsing. Generally web scraping will require that binary data be ignored - this usually means multimedia data or images - and then formatting the pieces that will confuse the desired goal - the text data. This means that in actually, optical character recognition software is a form of visual web scraper.

Usually a transfer of data occurring between two programs would utilize data structures designed to be processed automatically by computers, saving people from having to do this tedious job themselves. This usually involves formats and protocols with rigid structures that are therefore easy to parse, well documented, compact, and function to minimize duplication and ambiguity. In fact, they are so "computer-based" that they are generally not even readable by humans.

If human readability is desired, then the only automated way to accomplish this kind of a data transfer is by way of web scraping. At first, this was practiced in order to read the text data from the display screen of a computer. It was usually accomplished by reading the memory of the terminal via its auxiliary port, or through a connection between one computer's output port and another computer's input port.

It has therefore become a kind of way to parse the HTML text of web pages. The web scraping program is designed to process the text data that is of interest to the human reader, while identifying and removing any unwanted data, images, and formatting for the web design.

Though web scraping is often done for ethical reasons, it is frequently performed in order to swipe the data of "value" from another person or organization's website in order to apply it to someone else's - or to sabotage the original text altogether. Many efforts are now being put into place by webmasters in order to prevent this form of theft and vandalism.


Source: http://ezinearticles.com/?How-Your-Online-Information-is-Stolen---The-Art-of-Web-Scraping-and-Data-Harvesting&id=923976

Recover Data With Secure Data Recovery Services

Failure of hard disk drive, server, or RAID array can lead to loss of data stored in the computer and also stop ongoing work. Both these aspects can be extremely detrimental to the interests of the computer user, whether an individual or a business entity.

It is essential that at such a stage data recovery process is set in motion immediately to maximize the possibility of recovering the entire lost data and to make the computer operational. The first step would be to contact a reputable online services provider such as Secure Data Recovery Services. They have a network of it's locations throughout the United States.

Essential Attributes Of Data Recovery Services

If data recovery is of prime importance to you, choose the online recovery services that specialize in all types of them. These include hard drive, RAID recovery, Mac, SQL, and Tape recovery. You must ensure that the data one selected by you should be able to extract vital and critical data from any interface hard disk drive. For example, IDE, EIDE, SATA "Serial ATA," PATA "Parallel ATA," SCSI, SAS, and Fiber Channel. The data one should also be able to recover data from single drive, multiple-drive, and RAID array setups. They should also be able to service all major brand drives.

The most important attribute of Secure Data Recovery Services is that they have qualified, experienced, and professional technicians. They should be able to diagnose the cause of the failure and set it right. These technicians are trained to work continuously till the time a solution to your problem is found. The service also has all modern tools and instruments. The work is carried out in Clean Rooms so that no dust particle can enter the hard drive. All these services are provided to the full satisfaction of the clients and at competitive prices.

Loss of data can be a nightmare. Secure Data Recovery Services have the technical know how, experienced and qualified technicians, necessary tools, Clean Room, and the will to complete the recovery work as quickly as possible.


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How to Scrape Websites for Data without Programming Skills

Searching for data to back up your story? Just Google it, verify the accuracy of the source, and you’re done, right? Not quite. Accessing information to support our reporting is easier than ever, but very little information comes in a structured form that lends itself to easy analysis.

You may be fortunate enough to receive a spreadsheet from your local public health agency. But more often, you’re faced with lists or tables that aren’t so easily manipulated. It’s common for data to be presented in HTML tables — for instance, that’s how California’s Franchise Tax Board reports the top 250 taxpayers with state income tax delinquencies.

It’s not enough to copy those numbers into a story; what differentiates reporters from consumers is our ability to analyze data and spot trends. To make data easier to access, reorganize and sort, those figures must be pulled into a spreadsheet or database. The mechanism to do this is called Web scraping, and it’s been a part of computer science and information systems work for years.

It often takes a lot of time and effort to produce programs that extract the information, so this is a specialty. But what if there were a tool that didn’t require programming?

Enter OutWit Hub, a downloadable Firefox extension that allows you to point and click your way through different options to extract information from Web pages.

How to use OutWit Hub

When you fire it up, there will be a few simple options along the left sidebar. For instance, you can extract all the links on a given Web page (or set of pages), or all the images.

If you want to get more complex, head to the Automators>Scrapers section. You’ll see the source for the Web page. The tagged attributes in the source provide markers for certain types of elements that you may want to pull out.

Look through this code for the pattern common to the information you want to get out of the website. A certain piece of text or type of characters will usually be apparent. Once you find the pattern, put the appropriate info in the “Marker before” and “Marker after” columns. Then hit “Execute” and go to town.

An example: If you want to take out all the items in a bulleted list, use <li> as your before marker and </li> as your after marker. Or follow the same format with <td> and </td> to get items out of an HTML table. You can use multiple scrapers in OutWit Hub to pull out multiple columns of content.

There’s some solid help documentation to extend your ability to use OutWit Hub, with a variety of different tutorials.

If you want to extract more complicated information, you can. For instance, you can also pull out information from a series of similarly-formatted pages. The best way to do this is with the Format column in the scraper section to add a “regular expression,” a programmatic way to designate patterns. OutWit Hub has a tutorial on this, too.

OutWit Hub isn’t the only non-programming scraping option. If you want to get information out of Wikipedia and into a Google spreadsheet, for instance, you can.

But even when pushed to the max, OutWit Hub has its limitations. The simple truth is that using a programming language allows for more flexibility than any application that relies on pointing and clicking.

When you hit OutWit’s scraping limitations, and you’re interested in taking that next step, I recommend Dan Nguyen’s four-post tutorial on Web scraping, which also serves as an introduction to Ruby. Or use programmer Will Larson’s tutorial, which teaches you both about the ethics of scraping (Do you have the right to take that data? Are you putting undue stress on your source’s website?) while introducing the use of the Beautiful Soup library in Python.

Source: http://www.poynter.org/how-tos/digital-strategies/e-media-tidbits/102589/how-to-scrape-websites-for-data-without-programming-skills/

Outsource Data Mining Services to Offshore Data Entry Company

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

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

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

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

Why outsource your data entry requirements?

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

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

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

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

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

Why outsource data mining services?

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

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

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

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

Visit our Facebook Data Entry profile for comments & reviews.

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




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Possible That Less Prices For Web Data Scraping

Mark the market research organization or for any company to play an important role in the strategic decision making. Web scraping and data extraction technique used for business or other relevant data and information that are important tools. Many companies, self-copying and pasting information from the pages. Collect the data and is compared to the data to collect fresh troops were consumed in such a less time.

The data pertain to a CSV file, with the required format of the database, XML file or from any other source. Correlations and patterns in the data, so that the policies are designed for decision making. Where can I Yes, the known is the future.

The following are some examples of some data extraction;
And the competitive prices to interest rates it is pain, scraping the websites and the information
You use makeup or cat videos and pictures scraping web design use stock photography

Automatic data Collection
But the need for a collection of the United States on a regular basis. Those corporate market trends and trends to help customers get automated data collection techniques are very important.

These examples of targeted health care,

Product # shares for hourly
Competition in a daily basis Read deposits, financial institutions and from the various
Over time, a regular basis and the necessary

We’ve used the works of course you can deliver. This information can be downloaded from the database or spreadsheet analyzed and compared.

The data extraction function, it’s possible that prices will, Department of Commerce, developers, clinical data, the data and information in the stands of the foundation of the competitors.

Various forms of the arts and the data collection, and analysis, and after the lapse of such a sort period of time. For a little bit late in the Web market.

People that know good judgment and is willing to shave off the air soon. In this way, or this site, a large extent been the main reason is because of the football community. Most arts techniques considered unsavory.

In this way, we have a variety of websites and knowledge of the keyboard, do content right course as well defined. The process of or for the use of developers or all levels should be able to.

Various forms of the arts and the data collection, and analysis, and after the lapse of such a sort period of time. For a little bit late in the Web market.

People that know good judgment and is willing to shave off the air soon. In this way, or this site, a large extent been the main reason is because of the football community. Most arts techniques considered unsavory.

In this way, we have a variety of websites and knowledge of the keyboard, do content right course as well defined. The process of or for the use of developers or all levels should be able to. The process of data analysis, and cut off from such enterprises to the other functions of life. One is the great range of scale, because, in those skilled in military.

Welcome to crawling, the text, the fun, Dom parsing, and some of the common services for the methods of matching the course include some expresses. Parsers only process, HTML pages, or can be made by the sense annotations. To stay in the business world is to the purpose.


Source: http://articles.yourseofree.com/possible-that-less-prices-for-web-data-scraping/

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.


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