Friday 30 August 2013

Text Data Mining Can Be Profitable

There are billions of search terms performed on the internet every year,and the companies which make use of this vast amount of information are the ones who will be able to market effectively in the future. It is here that text data mining comes into its own, a technique which enables researchers to find patterns within groups of text which will enable them to make predictions as to how customers or other groups of people will act in the future. This article will take a look at text data mining and how we can help various groups of people to find the best things in the data analysis.

It is always a good idea to do some study of the text mining techniques before going on to text mining implementation, and this can be said to be especially true of the insurance industry where not only text mining but also generic data mining using in statistics can be a great help in determining profitability and also showing actuaries how to make future calculations.

Consultancy is an important part of text data mining, and the text mining consultant can bring a huge amount of knowledge to a company whatever the service or services that are providing, particularly if he has an extensive knowledge of text data mining technology and can help to build a system around it.

Of course it is not only commercial applications that can use text mining, because it also has used in security, in that it can help to track criminal intent on the Internet. There are also applications in the biomedical world, in order to help find clusters of data in the right way. But it is in the online world and in the field of marketing that text mining is being used extensively, particularly in customer relationship management [CRM] techniques, where the tools are among some of the most advanced.

Knowing how text mining algorithms work is essential for any consultant who works in this field, because it is an important tool in the marketing technique possibilities. By understanding how text data mining can help an organization a consultant or marketer can make great strides in profitability and this is something that most organizations would be glad for.



Source: http://ezinearticles.com/?Text-Data-Mining-Can-Be-Profitable&id=2314536

Tuesday 27 August 2013

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.



Source: http://ezinearticles.com/?Data-Extraction-Services---A-Helpful-Hand-For-Large-Organization&id=2477589

Monday 26 August 2013

Facts on Data Mining

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

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

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

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

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

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



Source: http://ezinearticles.com/?Facts-on-Data-Mining&id=3640795

Saturday 24 August 2013

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.



Source: http://ezinearticles.com/?New-Method-of-Market-Segmentation---Combining-Segmentation-With-Data-Mining&id=6890243

Friday 23 August 2013

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.


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

Thursday 22 August 2013

Business Intelligence Data Mining

Data mining can be technically defined as the automated extraction of hidden information from large databases for predictive analysis. In other words, it is the retrieval of useful information from large masses of data, which is also presented in an analyzed form for specific decision-making.

Data mining requires the use of mathematical algorithms and statistical techniques integrated with software tools. The final product is an easy-to-use software package that can be used even by non-mathematicians to effectively analyze the data they have. Data Mining is used in several applications like market research, consumer behavior, direct marketing, bioinformatics, genetics, text analysis, fraud detection, web site personalization, e-commerce, healthcare, customer relationship management, financial services and telecommunications.

Business intelligence data mining is used in market research, industry research, and for competitor analysis. It has applications in major industries like direct marketing, e-commerce, customer relationship management, healthcare, the oil and gas industry, scientific tests, genetics, telecommunications, financial services and utilities. BI uses various technologies like data mining, scorecarding, data warehouses, text mining, decision support systems, executive information systems, management information systems and geographic information systems for analyzing useful information for business decision making.

Business intelligence is a broader arena of decision-making that uses data mining as one of the tools. In fact, the use of data mining in BI makes the data more relevant in application. There are several kinds of data mining: text mining, web mining, social networks data mining, relational databases, pictorial data mining, audio data mining and video data mining, that are all used in business intelligence applications.

Some data mining tools used in BI 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 and so on.



Source: http://ezinearticles.com/?Business-Intelligence-Data-Mining&id=196648

Wednesday 21 August 2013

Data Mining

I just love the so called political correct terminology used today. How they decide it's really a political correct term is beyond me. Why don't they call it what it is; misleading terminology, whitewashing, sugar coating. Example: collaterial damage ie. innocent people fatally killed in the wake of combat.

Now the new term for collecting information on people to compile marketing lists so that we can all receive more junk mail, marketing phone calls and faxes is a cute little term called Data Mining.

This is a quote from a banking website on the subject:
Let me try to clarify this. We are wanting to contact our commercial customers' payors that do not bank with us. We would get the information off their checks when our commercial customers deposit them. For example, I use ABC Cleaners and pay by check but I bank at a different bank than the Cleaners. The Cleaner's bank would take my information off my check to contact me.

Data mining has been defined as "The nontrivial extraction of implicit, previously unknown, and potentially useful information from data" [1] and "The science of extracting useful information from large data sets or databases" [2]. Although it is usually used in relation to analysis of data, data mining, like artificial intelligence, is an umbrella term and is used with varied meaning in a wide range of contexts.

The Kirchman Corporation, a leading provider of automation software and compliance services to the banking industry, with over 800 financial institutions worldwide recently publised a 4 page gloss executive summary on Data Mining in the banking industry.

[The Kirchman Corporation became a Metavante subsidiary in May 2004 and operates within the Metavante Financial Services Group. Metavante is a subsidiary of Marshall & Ilsley Corporation (NYSE: MI) Kirchman Bankway®, the easiest-to-use and most customer-focused core bank software on the market, provides a comprehensive package of business solutions for use by the smallest de novo to the largest multi-billion-dollar bank holding company. Operating on IBM and Sun Microsystems hardware platforms, Kirchman Bankway® makes it easy for everyone from the teller to the CEO to access everything they need to know about their customers, right at their fingertips.[www.kirchman.com, Orlando. FL]

Data Mining software is used to analyse customer data and trends in banking as well as many other industries. Chase analyzed the attributes and habits of its checking account customers for clues that might reveal how to set the minimum balance requirement to retain profitable customers. The staff used data mining to develop profiles of customer groups whose members consistently had trouble maintaining minimum balances.

I'm sure you no where I'm headed with this. If Banks use Data Mining to predict trends in one area of services, it's not a far leap to say they would also use data mining to add courtesy bounce protection to customers who have a low balance and would be more likley to overdraft. Would it be too far of a leap to say banks might even use data mining in deciding what customers may get their account processed high to low?



Source: http://ezinearticles.com/?Data-Mining&id=12770

Saturday 17 August 2013

Basics of Web Data Mining and Challenges in Web Data Mining Process

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

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

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

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

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

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



Source: http://ezinearticles.com/?Basics-of-Web-Data-Mining-and-Challenges-in-Web-Data-Mining-Process&id=4937441

Friday 16 August 2013

Elevate Your Business With Data Entry Services

The sole aim of many organizations is to progress well in their objectives and hire people who are good and efficient in their work. However, sometimes, there are some work profiles that are mundane in nature but equally important like data entry services. You will be amazed to know that these services also play a crucial role in building the future of an organization.

In fact, with the coming of information technology, the data entry services have actually become a kind of industry, as various businesses need accurate and detailed information for various reasons. Thus they are relying on such services that not only help them in growing but are cost effective too. These data entry services are an asset for any organization irrespective of its size in both the terms of workforce, financial status and area. With the help of such services you are able to get the information on the market trends, your clients and moreover, about the status of your own business. Hence, there is a lot of demand for data entry services in order to do great business.

As you must be aware of the fact that data entry services can be time consuming; hence it requires efficient workforce to execute various tasks perfectly and diligently. Every transaction has to be recorded, processed and analyzed so that the management or the decision-makers can have a clear picture of the actual financial standing of the company. In fact, there are many organizations that are interested in the data of company so that they can strike a business deal with the company in the future; the competitors are also the one's who are constantly following the happenings of the company. However, the most important part that constitutes group are the shareholders, employees, creditors, consumers and the market in general. Therefore, this service plays a significant role in determining the future of the company. Thus, it is taken very seriously by many business enterprises for various reasons that can elevate their businesses by many fractions.

In fact, data entry services are now being outsourced from various leading vendors to further simplify the requirements of every business. Well, these services cover many business activities like document and image processing, data conversion, image enhancement, image editing, catalog processing, and photo manipulation. In fact, you can use data entry services for transferring hard or soft copy to any database format; insurance claims entry; PDF document indexing; online data capture; product catalogs to web based systems; online order entry and follow up; creation of new databases. Moreover, banks, airlines, government agencies, direct marketing services and service providers are using these services for better businesses.

The data services are also utilized for mailing lists; data mining and warehousing; data cleansing; audio transcriptions; legal documents; indexing of vouchers and documents; hand written ballot or card entry; online completion of surveys and responses of customers for various companies. Now its up to the company to whether go for a vendor or hire in-house staff to accomplish tasks in a better way; the main purpose of this service is to offer convenience that can help in curbing time as well as other resources.




Source: http://ezinearticles.com/?Elevate-Your-Business-With-Data-Entry-Services&id=777230

Wednesday 14 August 2013

Understanding Data Mining

Well begun is half done. We can say that the invention of Internet is the greatest invention of the century which allows for quick information retrieval. It also has negative aspects, as it is an open forum therefore differentiating facts from fiction seems tough. It is the objective of every researcher to know how to perform mining of data on the Internet for accuracy of data. There are a number of search engines that provide powerful search results.

Knowing File Extensions in Data Mining

For mining data the first thing is important to know file extensions. Sites ending with dot-com are either commercial or sales sites. Since sales is involved there is a possibility that the collected information is inaccurate. Sites ending with dot-gov are of government departments, and these sites are reviewed by professionals. Sites ending with dot-org are generally for non-profit organizations. There is a possibility that the information is not accurate. Sites ending with dot-edu are of educational institutions, where the information is sourced by professionals. If you do not have an understanding you may take help of professional data mining services.

Knowing Search Engine Limitations for Data Mining

Second step is to understand when performing data mining is that majority search engines have filtering, file extension, or parameter. These are restrictions to be typed after your search term, for example: if you key in "marketing" and click "search," every site will be listed from dot-com sites having the term "marketing" on its website. If you key in "marketing site.gov," (without the quotation marks) only government department sites will be listed. If you key in "marketing site:.org" only non-profit organizations in marketing will be listed. However, if you key in "marketing site:.edu" only educational sites in marketing will be displayed. Depending on the kind of data that you want to mine after your search term you will have to enter "site.xxx", where xxx will being replaced by.com,.gov,.org or.edu.

Advanced Parameters in Data Mining

When performing data mining it is crucial to understand far beyond file extension that it is even possible to search particular terms, for example: if you are data mining for structural engineer's association of California and you key in "association of California" without quotation marks the search engine will display hundreds of sites having "association" and "California" in their search keywords. If you key in "association of California" with quotation marks, the search engine will display only sites having exactly the phrase "association of California" within the text. If you type in "association of California" site:.com, the search engine will display only sites having "association of California" in the text, from only business organizations.

If you find it difficult it is better to outsource data mining to companies like Online Web Research Services



Source: http://ezinearticles.com/?Understanding-Data-Mining&id=5608012

Tuesday 13 August 2013

Know What the Truth Behind Data Mining Outsourcing Service

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

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

A wide range of services

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

Many companies fall

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

A lot of advantages

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

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



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

Sunday 11 August 2013

Internet Data Mining - How Does it Help Businesses?

Internet has become an indispensable medium for people to conduct different types of businesses and transactions too. This has given rise to the employment of different internet data mining tools and strategies so that they could better their main purpose of existence on the internet platform and also increase their customer base manifold.

Internet data-mining encompasses various processes of collecting and summarizing different data from various websites or webpage contents or make use of different login procedures so that they could identify various patterns. With the help of internet data-mining it becomes extremely easy to spot a potential competitor, pep up the customer support service on the website and make it more customers oriented.

There are different types of internet data_mining techniques which include content, usage and structure mining. Content mining focuses more on the subject matter that is present on a website which includes the video, audio, images and text. Usage mining focuses on a process where the servers report the aspects accessed by users through the server access logs. This data helps in creating an effective and an efficient website structure. Structure mining focuses on the nature of connection of the websites. This is effective in finding out the similarities between various websites.

Also known as web data_mining, with the aid of the tools and the techniques, one can predict the potential growth in a selective market regarding a specific product. Data gathering has never been so easy and one could make use of a variety of tools to gather data and that too in simpler methods. With the help of the data mining tools, screen scraping, web harvesting and web crawling have become very easy and requisite data can be put readily into a usable style and format. Gathering data from anywhere in the web has become as simple as saying 1-2-3. Internet data-mining tools therefore are effective predictors of the future trends that the business might take.



Source: http://ezinearticles.com/?Internet-Data-Mining---How-Does-it-Help-Businesses?&id=3860679

Friday 9 August 2013

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.



Source: http://ezinearticles.com/?Top-Data-Mining-Tools&id=1380551

Tuesday 6 August 2013

Data Entry Services For the Dynamic Webmaster

Data Entry Services is a fast growing industry. The universe of business is dynamic, fast paced, and in continual flux. In such an atmosphere the accessibility of precise, comprehensive information is a necessity. It is irrelevant whether you are a small business or a rambling universal empire, as information is an advantage in any set-up. The further you identify about the market, your consumers or trade, and other factors that power a corporation, the superior you can understand your own business.

There is typically an awe-inspiring quantity of DE required in accordance to development. In addition, DE services are also a requirement in this age of information, as information is vital in any organization. The need for data entry services is at a climax now as there are quite a lot of processes and confrontations present in any business today - these challenges include amalgamations, acquisitions, and new technological development.

The ease of access, value and assortment of information that an institute has at its removal are becoming gradually more imperative to consumers. Few of the examples of DE services are: data entry from manufactured goods catalogs to website based systems; data entry from hard/soft copy to any database layout; insurance claims entry; PDF document indexing; online data capture; data input from images; online order input and tracking; creation of novel databases; and postings to accessible databases for financing institutions, airlines, government bureau's, uninterrupted marketing services and service contributors; Web-based indexed documents retrieval services; help and assistance; mailing lists; data mining and warehousing; information cleansing; audio transcriptions; officially permitted documents; indexing of checks and documents; hand written card entry; online completion of surveys and reactions of consumers for an assortment of clients, at call centers and so on. The list is perceptibly never ending. A further attribute of the popular data entry services which can be carried out from a home office is entries for accounting or bookkeeping businesses.



Source: http://ezinearticles.com/?Data-Entry-Services-For-the-Dynamic-Webmaster&id=3733360

Monday 5 August 2013

Data Entry - Outsourcing the Answer to Data Entry Solution Needs

Data entry is the process of systematic and accurate copying of information by keying and scanning text, images and numerical documents into a client preferred format and data base. It is not a primary business activity and function. However smooth, efficient and competent data entry solution is required to stay competitive and to ensure customer satisfaction because businesses accumulate huge volume of information in their day to day operation.

Contrary to common views data entry is not a simple and effortless task. It involves many activities which ranges from simple to complex and to name a few we have image scanning for electronic filing, book entry, making product catalogs, indexing, claims and invoice forms entry, company reports entry, medical transcription, research and data mining, document reformatting, proof reading and updating documents related to customer information. It is a tedious job that is not only time consuming to accomplish but also requires skills and competence.

To save overhead costs companies have farmed out or outsourced noncore jobs such as data entry to countries like Philippines and India. These countries are known for their rich and inexpensive intellectual capital. Outsourcing is much more cost effective than hiring full-time employees because companies will not be paying for medical insurances, vacation leave, bonuses and other fringe benefits on top of competitive salaries. There are also other advantages in outsourcing. It also helps companies focus in their core business activities, there will be a quick turnaround time for projects and high quality of work is assured, it reduces management problems and companies can take advantage of competitive labor resources worldwide.

The National Data Entry has qualified members who can provide services to help you in data management care needs. Its membership is very diverse. They have members coming from all parts of the world from the U.S to Southeast Asia. You may enlist your company in this membership site as a job provider and for more information just browse their website in the internet. You do not have to search far and wide to get skilled, efficient but inexpensive service providers.


Source: http://ezinearticles.com/?Data-Entry---Outsourcing-the-Answer-to-Data-Entry-Solution-Needs&id=3405628

Friday 2 August 2013

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

Thursday 1 August 2013

Web Data Extraction Services

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

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

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

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

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

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

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


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