New Method of Market Segmentation - Combining Segmentation With Data Mining

Marketers have the ability to get high-fidelity information on their target markets through market segmentation. Market segmentation is the process of categorizing potential customers based on certain variables, such as age, gender, and income. A market segment is a group of customers that will react in the same way to a particular marketing campaign. By gathering this information, marketers can tailor their campaigns to groups of prospects to build stronger relationships with them.

Marketers gather this demographic information through surveys, usually when the customer submits a product rebate or willingly participates in a customer satisfaction survey. Over the majority of the past few decades, market segmentation consisted of differentiating prospects based on very simple variables: income, race, location, etc. While this is definitely important information to have on your target market, modern market segmentation takes into account more integrated information.

Modern segmentation breaks the market into target clusters that take into account not only standard demographics, but also other factors such as population density, psychographics, and buying and spending habits of customers. By focusing on these variables in addition to standard demographics, you can gain deeper insight into customer behavior.

Using standard demographics, you can tailor your marketing pieces to specific groups of people. But, by including these more sophisticated variables in your segmentation process, you can determine achieve a higher degree of "lift" or return on your segmentation efforts.

Segmenting your market on these factors helps you realize your total opportunity and revenue potential. It can enable you to better compete with similar product or service providers and lets you know where you stand within the game. It can help you target untapped market opportunities and allow you to better reach and retain customers.

Market segmentation depends on the gathering of high-quality, usable data. Many companies exist to gather and sell massive databases of targeted customer information, as well as providing consultation services to help you make sense of data bought or already owned. The key to the process is determining the best way to split up data.

There are essentially two methods for categorizing customers. Segments can either be determined in advance and then customers are assigned to each segment, or the actual customer data can be analyzed to identify naturally occurring behavioral clusters. Each cluster forms a particular market segment.

The benefit of cluster-based segmentation is that as a market's behavior changes, you can adapt your campaigns to better suit the cluster. The latest techniques blend cluster-based segmentation with deeper customer information acquired via data mining. Data mining uses algorithms to interrogate data within a database, and can produce information such as buying frequency and product types.

This new method of market segmentation, combining segmentation with data mining, provides marketers with high quality information on how their customers shop for and purchase their products or services. By combining standard market segmentation with data mining techniques you can better predict and model the behavior of your segments.


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The Increasing Significance of Data Entry Services

The instantaneous business environment has become extremely competitive in the new era of globalization. Huge business behemoths that had been benefited from monopolistic luxuries are now being challenged by newer participant in the marketplace, forcing recognized players to reorganize their plans and strategies. These are some of the major reasons that seemed to have forced businesses to opt for outsourcing services such as data entry services that allow them to focus on their core business processes. This in turn makes it simple for them to attain and maintain business competencies, a prerequisite for effectively overcoming the rising competitive challenges.

So, how exactly is data entry helping businesses in achieving their targeted goals and objectives? Well, to be able to know actually that, we will first have to delve deeper into the field of data entry and allied activities. To start with, it would be worth mentioning that every business, big and small, generates voluminous amounts of data and information that is important from a business point of view. This is exactly where the problems start to surface because accessing, analyzing and processing such voluminous amounts of data is too time consuming and obviously a task that can easily be classified as non-productive. And these are exactly the reasons for outsourcing such non-core work processes to third party outsourcing firms.

There is many data entry outsourcing firms and most of them are located in developing countries such as India. There are many reasons for such regional clustering, but the most prominent reason it seems is that India has a vast talent pool, comprising of educated, English-speaking professionals. The best part is that it is relatively less expensive to hire the services of these professionals. The same level of expertise will have been a lot more expensive to hire if it had been in a developed country. Subsequently, more and more businesses worldwide are outsourcing their non-core work processes.

As Globalization intensifies even more in the coming years, businesses will face even greater amounts of competitive pressures and it will just not be possible for them to even think about managing everything on their own, let alone actually going ahead and doing it. However, that should not be a problem, especially for businesses that opt for outsourcing services such as data entry and data conversion. By hiring such high-end and cost-effective services, these businesses will be able to realize the associated benefits that will come mostly as significant cost reductions, optimum accuracy, and increased efficiencies.

So for business executives that think outsourcing data entry related processes can help to achieve your targeted business goals and objectives, it's time you contacted an offshore outsourcing provider and request them precisely how they can ease your business. However just make sure that you opt for the most excellent available data entry services provider, perceptibly because it will be like sharing a part of your business.


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Data Entry Services Help to Maintain Data Correctly

Data of any big or small organizations should be properly maintained. Any mistake on the data entry may prove blunder for the company. All companies have a separate branch that maintains all the datas. In an organization there are various types of data that need to be maintained. It is most commonly found that the data entered by the in-house staff are not accurate and they always do some sort of mistakes. There are many counties in the world that provide data entry services. The service offered by them is error free and up-to-date. The service provided by a reputed firm is commendable. If a company feels problem in maintaining records then it can hire a reputed private firm or an experienced individual.

In this modern world, data entry is the most fundamental and internal function of every business firms. Many companies expertise in the field of providing the services. A company will prosper only when the data of an organization is properly maintained. To get the data entry service from an expertise country will save time, save money and one will get quick service. Off shoring the service from some other company is much more reliable and one can get a quality work. It is the best option today. Data entry from product catalogs to web based systems, from hard/soft copy to any database format, online order entry and creation of new databases are some of the examples of the data entry.

There are many countries that provide data entry services. Depending on the necessity of the company, one can hire a private firm or hire an individual for maintaining all the datas. The services provided by India are excellent and many countries are lined up to take its service. The professionals of India are very excellent and enable to manage, integrate, analyze and secure any critical data. They provide industry's best service. It is a very tiring job and one need to be very much attentive in inserting those n numbers of data. If you want to seek the service from any private firm or an individual and you are totally naïve in this matter then internet can help you out. It will give information about the various companies across the world that provides quality data service.

These services offer outsource data entry, data entry outsource, outsourcing data entry, data entry outsourcing, offshore data entry, data entry companies. If you hire a reputed firm that provides excellent services then all your tension will get over. You will feel relax as all the affairs of your company is very systematically maintained. A very proficient person is required to maintain those datas. Most of the companies opt for this service. This service is a blessing for any big and small organization as it will keep all the records correctly. Today, most of the companies rely on this service. This sort of service reduces labor cost and gives an excellent result. Its advantage is endless.



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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.


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Data Mining As a Process

The data mining process is also known as knowledge discovery. It can be defined as the process of analyzing data from different perspectives and then summarizing the data into useful information in order to improve the revenue and cut the costs. The process enables categorization of data and the summary of the relationships is identified. When viewed in technical terms, the process can be defined as finding correlations or patterns in large relational databases. In this article, we look at how data mining works its innovations, the needed technological infrastructures and the tools such as phone validation.

Data mining is a relatively new term used in the data collection field. The process is very old but has evolved over the time. Companies have been able to use computers to shift over the large amounts of data for many years. The process has been used widely by the marketing firms in conducting market research. Through analysis, it is possible to define the regularity of customers shopping. How the items are bought. It is also possible to collect information needed for the establishment of revenue increase platform. Nowadays, what aides the process is the affordable and easy disk storage, computer processing power and applications developed.

Data extraction is commonly used by the companies that are after maintaining a stronger customer focus no matter where they are engaged. Most companies are engaged in retail, marketing, finance or communication. Through this process, it is possible to determine the different relationships between the varying factors. The varying factors include staffing, product positioning, pricing, social demographics, and market competition.

A data-mining program can be used. It is important note that the data mining applications vary in types. Some of the types include machine learning, statistical, and neural networks. The program is interested in any of the following four types of relationships: clusters (in this case the data is grouped in relation to the consumer preferences or logical relationships), classes (in this the data is stored and finds its use in the location of data in the per-determined groups), sequential patterns (in this case the data is used to estimate the behavioral patterns and patterns), and associations (data is used to identify associations).

In knowledge discovery, there are different levels of data analysis and they include genetic algorithms, artificial neural networks, nearest neighbor method, data visualization, decision trees, and rule induction. The level of analysis used depends on the data that is visualized and the output needed.

Nowadays, data extraction programs are readily available in different sizes from PC platforms, mainframe, and client/server. In the enterprise-wide uses, size ranges from the 10 GB to more than 11 TB. It is important to note that two crucial technological drivers are needed and are query complexity and, database size. When more data is needed to be processed and maintained, then a more powerful system is needed that can handle complex and greater queries.

With the emergence of professional data mining companies, the costs associated with process such as web data extraction, web scraping, web crawling and web data mining have greatly being made affordable.



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Data Extraction Services - A Helpful Hand For Large Organization

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

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

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

The different types of Data Extraction Services:

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

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

Advantages of Outsourcing Data Extraction Services:

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

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


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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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Data Mining - Critical for Businesses to Tap the Unexplored Market

Knowledge discovery in databases (KDD) is an emerging field and is increasingly gaining importance in today's business. The knowledge discovery process, however, is vast, involving understanding of the business and its requirements, data selection, processing, mining and evaluation or interpretation; it does not have any pre-defined set of rules to go about solving a problem. Among the other stages, the data mining process holds high importance as the task involves identification of new patterns that have not been detected earlier from the dataset. This is relatively a broad concept involving web mining, text mining, online mining etc.

What Data Mining is and what it is not?

The data mining is the process of extracting information, which has been collected, analyzed and prepared, from the dataset and identifying new patterns from that information. At this juncture, it is also important to understand what it is not. The concept is often misunderstood for knowledge gathering, processing, analysis and interpretation/ inference derivation. While these processes are absolutely not data mining, they are very much necessary for its successful implementation.

The 'First-mover Advantage'

One of the major goals of the data mining process is to identify an unknown or rather unexplored segment that had always existed in the business or industry, but was overlooked. The process, when done meticulously using appropriate techniques, could even make way for niche segments providing companies the first-mover advantage. In any industry, the first-mover would bag the maximum benefits and exploit resources besides setting standards for other players to follow. The whole process is thus considered to be a worthy approach to identify unknown segments.

The online knowledge collection and research is the concept involving many complications and, therefore, outsourcing the data mining services often proves viable for large companies that cannot devote time for the task. Outsourcing the web mining services or text mining services would save an organization's productive time which would otherwise be spent in researching.

The data mining algorithms and challenges

Every data mining task follows certain algorithms using statistical methods, cluster analysis or decision tree techniques. However, there is no single universally accepted technique that can be adopted for all. Rather, the process completely depends on the nature of the business, industry and its requirements. Thus, appropriate methods have to be chosen depending upon the business operations.

The whole process is a subset of knowledge discovery process and as such involves different challenges. Analysis and preparation of dataset is very crucial as the well-researched material could assist in extracting only the relevant yet unidentified information useful for the business. Hence, the analysis of the gathered material and preparation of dataset, which also considers industrial standards during the process, would consume more time and labor. Investment is another major challenge in the process as it involves huge cost on deploying professionals with adequate domain knowledge plus knowledge on statistical and technological aspects.

The importance of maintaining a comprehensive database prompted the need for data mining which, in turn, paved way for niche concepts. Though the concept has been present for years now, companies faced with ever growing competition have realized its importance only in the recent years. Besides being relevant, the dataset from where the information is actually extracted also has to be sufficient enough so as to pull out and identify a new dimension. Yet, a standardized approach would result in better understanding and implementation of the newly identified patterns.


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Top Data Mining Tools

Data mining is important because it means pulling out critical information from vast amounts of data. The key is to find the right tools used for the expressed purposes of examining data from any number of viewpoints and effectively summarize it into a useful data set.

Many of the tools used to organize this data have become computer based and are typically referred to as knowledge discovery tools.

Listed below are the top data mining tools in the industry:

    Insightful Miner - This tool has the best selection of ETL functions of any data mining tool on the market. This allows the merging, appending, sorting and filtering of data.
    SQL Server 2005 Data Mining Add-ins for Office 2007 - These are great add-ins for taking advantage of SQL Server 2005 predictive analytics in Office Excel 2007 and Office Visio 2007. The add-ins Allow you to go through the entire development lifecycle within Excel 2007 by using either a spreadsheet or external data accessible through your SQL Server 2005 Analysis Services instance.
    Rapidminder - Also known as YALE is a pretty comprehensive and arguably world-leading when it comes to an open-source data mining solution. it is widely used from a large number of companies an organizations. Even though it is open-source, this tool, out of the box provides a secure environment and provides enterprise capable support and services so you will not be left out in the cold.

The list is short but ever changing in order to meet the increasing demands of companies to provide useful information from years of data.


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Searching the Web Using Text Mining and Data Mining

There are many types of financial analysis tools that are useful for various purposes. Most of these are easily available online. Two such tools of software for financial analysis include the text mining and data mining. Both methods have been discussed in details in the following section.

The features of Text Mining It is a way by which information of high-quality can be derived from a text. It involves giving structure to the input text then deriving patterns within the data that has been structured. Finally, the process of evaluating and interpreting the output is undertaken.

This form of mining usually involves the process of structuring the text input, and deriving patterns within the structured data, and finally evaluating and interpreting the data. It differs from the way we are familiar with in searching the web. The goal of this method is to find unknown information. It can be done with analyses in topics that that were not researched before.

What is Data Mining? It is the process of the extraction of patterns from the data. Nowadays, it has become very vital to transform this data into information. It is particularly used in marketing practices as well as fraud detection and surveillance. We can extract hidden information from huge databases of information. It can be used to predict future trends as well as to aid the company business to make knowledgeable quick decisions.

Working of data mining: Modeling technique is used to perform the operation of such form of mining. For these techniques, you must need to be fully integrated with a data warehouse as well as financial analysis tools. Some of the areas where this method is used are:

    Pharmaceutical companies which need to analyze its sales force and to achieve their targets.
    Credit card companies and transportation companies with sales force.
    Also large consumer goods companies use such mining techniques.
    With this method, a retailer may utilize POS or point-of-sale data of customer purchases in order to develop strategies for sale promotion.

The major elements of Data mining:

1. Extracting, transforming, and sending load transaction data on the data warehouse of the server system.

2. Storing and managing the data in for database systems that are multidimensional in nature.

3. Presenting data to the IT professionals and business analysts for processing.

4. Presenting the data to the application software for analyses.

5. Presentation of the data in dynamic ways like graph or table.

The main point of difference between the two types of mining is that text mining checks the patterns from natural text instead of databases where the data is structured.

Data mining software supports the entire process of such mining and discovery of knowledge. These are available on the internet. Data mining software serves as one of the best financial analysis tools. You can avail of data mining software suites and their reviews freely over the internet and easily compare between them.


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Data Entry Services by a Virtual Assistant

Data Entry is a basic requirement for any business and it may appear to be simple to supervise and handle, this engage a lot of procedures that require a proper handling. Enormous modifications have taken place in the field of data entry and because of this data processing work has become really easier then before. So if you are looking to make data entry services useful to maintain the information and data of your company, you need a skilled virtual assistant. These days it is almost impossible to say Data Entry Services are costly; however, the fact is this by outsourcing a data process to country like India will be a good option for an organization to find a quality services with cost-effective solutions. All you need to choose you will hire a VA for the job you wanted to complete within a particular time frame, with quality and a cost-effective solution or to hire an in house employee for which you have to pay employee benefits such as sick pay, employee insurance, vacation pay, worker's compensation and much more. You are the best person to decide, you want to outsource the job to a virtual assistant who only charge for the job they work for after all this is your business.

Data Entry is one of the important features for your business and as a result you must make sure that this is dealt in a right direction. Outsourcing Data Entry service to a virtual assistant is not only a part of a business. With the enormous flow on the ground of Information Technology Data Conversion service is evenly significant. Data Conversion is the process to renovate the data in which data is converted from file source to another file type such as extracting the data from PDF file to excel spreadsheet and business world need these conversion for efficiency in performance. Virtual Assistant's are skilled enough to convert almost any file type to another for a business owner to access the data in any format.

By outsourcing your data entry jobs to a virtual assistant in India has been found very cost-effective solutions with quality of the job. Outsourcing Data Entry Services is one of the rise these days and the reason behind this is business owners has enjoyed the success of outsourcing the job to a virtual assistant. The major benefit of getting data entry services complete by a virtual assistant in India is they work really cheap and the work done by them is of top quality job. So if the data entry services provided by a virtual assistant are cheap and of top quality there is completely no possibility why someone would not take the benefits of a VA services.

Amit Ganotra is a skilled virtual assistant providing services like Data Entry, Data Processing, Data Conversion, Data Mining, Data cleaning, OCR Cleanup, Article Submission, Directory Submissions, Web Development. For more information about the services we provide please visit the website.


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Data Entry Outsourcing Companies

Data entry outsourcing companies are there to help firms and organizations with their data entry needs. As the numbers of clients of companies grow each day, the amount of data accumulated is increasing to and in order to help the development of the company it is essential that all data collected be grouped and ordered so that they can be studied. This is where data entry outsourcing companies come in, they have dedicated teams of individuals that specialize in this field and are familiar with the different software out there for such business needs.

Hiring one of these outsourcing companies is popular because they are highly cost effective. There are a large number of other benefits that come with hiring an outside professional to do the data entry work for you. The team of workers that they have are professionals and often have years of experience of doing jobs like the one you want to them do, making them efficient. They generally have years to build up speed and accuracy, two vital skills that such outsourcing companies must possess. Data entry outsourcing companies also have better time management, which basically means that they are able to meet all deadlines, which is mostly led by market competitiveness but translates into faster results for you.

Data entry could be simple tabulation of numbers, like those for finances, or a collection of customer details; it could be of the forms processing kind where forms that have been filled by potential customers are analyzed and only relevant data is filled into the database, it could be of the images processing kinds, where the client provides images of sheets of paper, or flow charts and it is the job of the outsourcing company to convert all the above data that the client provides into tabulated or charted format for easy analysis.

Besides the standard kinds of services, data entry outsourcing companies also provide other services like data scrubbing, which is correction of old data according to change in the time period, data alignment, which proper sorting out of data, data standardization, which is done in cases when the data is spread out over a large number of files and databases and needs to be collected in one place and data de-duplication, which is done when there are repetitions in the data entered leading to discrepancies. Learn more about how such outsourcing companies can help you.


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Data Mining Tools - Understanding Data Mining

Data mining basically means pulling out important information from huge volume of data. Data mining tools are used for the purposes of examining the data from various viewpoints and summarizing it into a useful database library. However, lately these tools have become computer based applications in order to handle the growing amount of data. They are also sometimes referred to as knowledge discovery tools.

As a concept, data mining has always existed since the past and manual processes were used as data mining tools. Later with the advent of fast processing computers, analytical software tools, and increased storage capacities automated tools were developed, which drastically improved the accuracy of analysis, data mining speed, and also brought down the costs of operation. These methods of data mining are essentially employed to facilitate following major elements:

    Pull out, convert, and load data to a data warehouse system
    Collect and handle the data in a database system
    Allow the concerned personnel to retrieve the data
    Data analysis
    Data presentation in a format that can be easily interpreted for further decision making

We use these methods of mining data to explore the correlations, associations, and trends in the stored data that are generally based on the following types of relationships:

    Associations - simple relationships between the data
    Clusters - logical correlations are used to categorise the collected data
    Classes - certain predefined groups are drawn out and then data within the stored information is searched based on these groups
    Sequential patterns - this helps to predict a particular behavior based on the trends observed in the stored data

Industries which cater heavily to consumers in retail, financial, entertainment, sports, hospitality and so on rely on these data methods of obtaining fast answers to questions to improve their business. The tools help them to study to the buying patterns of their consumers and hence plan a strategy for the future to improve sales. For e.g. restaurant might want to study the eating habits of their consumers at various times during the day. The data would then help them in deciding on the menu at different times of the day. Data mining tools certainly help a great deal when drawing out business plans, advertising strategies, discount plans, and so on. Some important factors to consider when selecting a data mining tool include the platforms supported, algorithms on which they work (neural networks, decisions trees), input and output options for data, database structure and storage required, usability and ease of operation, automation processes, and reporting methods.


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Three Common Methods For Web Data Extraction

Probably the most common technique used traditionally to extract data from web pages this is to cook up some regular expressions that match the pieces you want (e.g., URL's and link titles). Our screen-scraper software actually started out as an application written in Perl for this very reason. In addition to regular expressions, you might also use some code written in something like Java or Active Server Pages to parse out larger chunks of text. Using raw regular expressions to pull out the data can be a little intimidating to the uninitiated, and can get a bit messy when a script contains a lot of them. At the same time, if you're already familiar with regular expressions, and your scraping project is relatively small, they can be a great solution.

Other techniques for getting the data out can get very sophisticated as algorithms that make use of artificial intelligence and such are applied to the page. Some programs will actually analyze the semantic content of an HTML page, then intelligently pull out the pieces that are of interest. Still other approaches deal with developing "ontologies", or hierarchical vocabularies intended to represent the content domain.

There are a number of companies (including our own) that offer commercial applications specifically intended to do screen-scraping. The applications vary quite a bit, but for medium to large-sized projects they're often a good solution. Each one will have its own learning curve, so you should plan on taking time to learn the ins and outs of a new application. Especially if you plan on doing a fair amount of screen-scraping it's probably a good idea to at least shop around for a screen-scraping application, as it will likely save you time and money in the long run.

So what's the best approach to data extraction? It really depends on what your needs are, and what resources you have at your disposal. Here are some of the pros and cons of the various approaches, as well as suggestions on when you might use each one:

Raw regular expressions and code

Advantages:

- If you're already familiar with regular expressions and at least one programming language, this can be a quick solution.

- Regular expressions allow for a fair amount of "fuzziness" in the matching such that minor changes to the content won't break them.

- You likely don't need to learn any new languages or tools (again, assuming you're already familiar with regular expressions and a programming language).

- Regular expressions are supported in almost all modern programming languages. Heck, even VBScript has a regular expression engine. It's also nice because the various regular expression implementations don't vary too significantly in their syntax.

Disadvantages:

- They can be complex for those that don't have a lot of experience with them. Learning regular expressions isn't like going from Perl to Java. It's more like going from Perl to XSLT, where you have to wrap your mind around a completely different way of viewing the problem.

- They're often confusing to analyze. Take a look through some of the regular expressions people have created to match something as simple as an email address and you'll see what I mean.

- If the content you're trying to match changes (e.g., they change the web page by adding a new "font" tag) you'll likely need to update your regular expressions to account for the change.

- The data discovery portion of the process (traversing various web pages to get to the page containing the data you want) will still need to be handled, and can get fairly complex if you need to deal with cookies and such.

When to use this approach: You'll most likely use straight regular expressions in screen-scraping when you have a small job you want to get done quickly. Especially if you already know regular expressions, there's no sense in getting into other tools if all you need to do is pull some news headlines off of a site.

Ontologies and artificial intelligence

Advantages:

- You create it once and it can more or less extract the data from any page within the content domain you're targeting.

- The data model is generally built in. For example, if you're extracting data about cars from web sites the extraction engine already knows what the make, model, and price are, so it can easily map them to existing data structures (e.g., insert the data into the correct locations in your database).

- There is relatively little long-term maintenance required. As web sites change you likely will need to do very little to your extraction engine in order to account for the changes.

Disadvantages:

- It's relatively complex to create and work with such an engine. The level of expertise required to even understand an extraction engine that uses artificial intelligence and ontologies is much higher than what is required to deal with regular expressions.

- These types of engines are expensive to build. There are commercial offerings that will give you the basis for doing this type of data extraction, but you still need to configure them to work with the specific content domain you're targeting.

- You still have to deal with the data discovery portion of the process, which may not fit as well with this approach (meaning you may have to create an entirely separate engine to handle data discovery). Data discovery is the process of crawling web sites such that you arrive at the pages where you want to extract data.

When to use this approach: Typically you'll only get into ontologies and artificial intelligence when you're planning on extracting information from a very large number of sources. It also makes sense to do this when the data you're trying to extract is in a very unstructured format (e.g., newspaper classified ads). In cases where the data is very structured (meaning there are clear labels identifying the various data fields), it may make more sense to go with regular expressions or a screen-scraping application.

Screen-scraping software

Advantages:

- Abstracts most of the complicated stuff away. You can do some pretty sophisticated things in most screen-scraping applications without knowing anything about regular expressions, HTTP, or cookies.

- Dramatically reduces the amount of time required to set up a site to be scraped. Once you learn a particular screen-scraping application the amount of time it requires to scrape sites vs. other methods is significantly lowered.

- Support from a commercial company. If you run into trouble while using a commercial screen-scraping application, chances are there are support forums and help lines where you can get assistance.

Disadvantages:

- The learning curve. Each screen-scraping application has its own way of going about things. This may imply learning a new scripting language in addition to familiarizing yourself with how the core application works.

- A potential cost. Most ready-to-go screen-scraping applications are commercial, so you'll likely be paying in dollars as well as time for this solution.

- A proprietary approach. Any time you use a proprietary application to solve a computing problem (and proprietary is obviously a matter of degree) you're locking yourself into using that approach. This may or may not be a big deal, but you should at least consider how well the application you're using will integrate with other software applications you currently have. For example, once the screen-scraping application has extracted the data how easy is it for you to get to that data from your own code?

When to use this approach: Screen-scraping applications vary widely in their ease-of-use, price, and suitability to tackle a broad range of scenarios. Chances are, though, that if you don't mind paying a bit, you can save yourself a significant amount of time by using one. If you're doing a quick scrape of a single page you can use just about any language with regular expressions. If you want to extract data from hundreds of web sites that are all formatted differently you're probably better off investing in a complex system that uses ontologies and/or artificial intelligence. For just about everything else, though, you may want to consider investing in an application specifically designed for screen-scraping.

As an aside, I thought I should also mention a recent project we've been involved with that has actually required a hybrid approach of two of the aforementioned methods. We're currently working on a project that deals with extracting newspaper classified ads. The data in classifieds is about as unstructured as you can get. For example, in a real estate ad the term "number of bedrooms" can be written about 25 different ways. The data extraction portion of the process is one that lends itself well to an ontologies-based approach, which is what we've done. However, we still had to handle the data discovery portion. We decided to use screen-scraper for that, and it's handling it just great. The basic process is that screen-scraper traverses the various pages of the site, pulling out raw chunks of data that constitute the classified ads. These ads then get passed to code we've written that uses ontologies in order to extract out the individual pieces we're after. Once the data has been extracted we then insert it into a database.


Source: http://ezinearticles.com/?Three-Common-Methods-For-Web-Data-Extraction&id=165416

Work From Home Data Entry Opportunities For You

Working from home gives you tremendous control over your working environment, and your working experience. Your working hours are more flexible, allowing you to live your life the way you want to, while generating income. One of the most flexible, and popular, work from home opportunities is data entry. However, with an increasing amount of scams appearing on the internet, it is advisable to proceed cautiously when looking for work from home data entry positions.

Before you begin your search, it is important to understand what a data entry job is. A data entry position should require you to fill out forms. Some of these forms may require an internet connection to be accessed, some may not. However, most of these forms require a connection to the internet. Make no mistake; a certain amount of work is required before you start making money. It would be unrealistic to join a program and expect to make money by not doing anything.

But why would companies outsource data entry positions? Companies occasionally outsource data entry positions to save on cost. They save money as the outsourced positions generally become performance based; you are paid according to how much work you do. This saves them money, as they no longer have to pay an employee a fixed income, or provide said employee with perks and benefits.

Some work from home data entry positions will give you the freedom to select the companies you wish to work for. Most of these programs will also require a joining fee, which presents another challenge when selecting a data entry position; the validity of the program.

There are several reasons as to why a sign up fee is required. Firstly, some of these websites act as middlemen between the companies and the freelance data entry personnel. These websites have operating costs that need to be met. They have staff to pay, overheads to reach and profits that need to be made.

In order to attract companies to their service, they may offer their services to these companies free of charge. After building a wide network of companies, they 'sell' the opportunity to work for these companies to would-be work from home enthusiasts. And that's how they make money by selling these programs.

However, not all of these websites are legitimate. Several of them are pyramid schemes looking to rob you of your money. With the ever changing internet landscape, it's important to be able to identify a scam, regardless of its form. If you require some clarity on a program you are interested in joining, you should search for feedback regarding the site in question.

Forums are an excellent place to start. There are also several experts who would be more than willing to provide opinions and advice. E-mailing them is a simple solution that could help you find your dream job, while saving you money. And finally, there are reports that you can purchase. These 'tell-all' reports can be brutally honest and highly informative. These reports can give you an edge in avoiding scams and finding a genuine data entry position.

Work from home data entry is a feasible method of generating income. Just ensure that you thread carefully along the mine-filled path that is online 'data entry' and you'll be able to find the ideal position for you.


Source: http://ezinearticles.com/?Work-From-Home-Data-Entry-Opportunities-For-You&id=1389769

Data Entry Services Help Your Business Flow Smoothly

A business comes into existence with the sole motive of earning profits and a business owner will take all steps within his means to ensure that work keeps on flowing smoothly and the optimum utilization of resources takes place. Every division in the organization is created with the objective of catalyzing the growth and not causing a hindrance to the progress of the business. Hence it is important to consider each division carefully and analyze if any further optimization can be undertaken at any level. The finance division of a business is one of the most crucial aspects of any organization. It is responsible for maintaining a check and keeping a record of each and every transaction that takes place in the day to day running of the business by data entry services provided by professionals or in-house accounts personnel. This ensures that necessary information regarding the plans; strategies and policies of the organization are available at a moment's notice to facilitate decision-making by the senior management.

Data entry services by professionals appointed for this task play a crucial role in running a business successfully. It makes a major difference in the performance standards of any business. Outsourcing a competent firm for providing your business with data entry services helps you in optimization of resources that were earlier being invested in the accounts department to take care of this crucial need of the business. Data entry services provided by experienced professionals help your business to save time and money and help the organization to increase the pace of regular business activities. The other competitive advantage provided by the data entry services include the ready availability of accurate and authentic at any given point that helps to facilitate decision making for profit creation and expansion of the business. Accurate data maintained on a daily basis and transferred online to the organization help the business to keep track of each expense incurred and profit gained thereby enabling the business to chart out the next course of action.

Data entry services are provided by professionally competent firms who hire experienced individuals to cater to the requirements of every individual client. The data entry services are usually provided round the clock to ensure that the client does not have to wait or face delays when the data is urgently required. The data entry services are provided by vendors who have years of experience, advanced technology and software to carry out the work and required flexibility to accommodate the needs of the client. It is therefore a viable option for any business irrespective of whether it is small or a big corporation. Data entry services, though not complex in nature, but are highly time consuming and this is the prime reason why companies need to outsource this service to cut down on the cost spend on hiring data entry professionals on the company payroll. The data entry services provided by a reputed vendor will ensure that you have highly accurate data properly accumulated for your reference while the confidentiality of your data is also assured. Hence outsourcing data entry services might be the best option for any business in this competitive world.


Source: http://ezinearticles.com/?Data-Entry-Services-Help-Your-Business-Flow-Smoothly&id=641783