Digging Up Dollars With Data Mining - An Executive's Guide

Traditionally, organizations use data tactically - to manage operations. For a competitive edge, strong organizations use data strategically - to expand the business, to improve profitability, to reduce costs, and to market more effectively. Data mining (DM) creates information assets that an organization can leverage to achieve these strategic objectives.

In this article, we address some of the key questions executives have about data mining. These include:

    What is data mining?
    What can it do for my organization?
    How can my organization get started?

Business Definition of Data Mining

Data mining is a new component in an enterprise's decision support system (DSS) architecture. It complements and interlocks with other DSS capabilities such as query and reporting, on-line analytical processing (OLAP), data visualization, and traditional statistical analysis. These other DSS technologies are generally retrospective. They provide reports, tables, and graphs of what happened in the past. A user who knows what she's looking for can answer specific questions like: "How many new accounts were opened in the Midwest region last quarter," "Which stores had the largest change in revenues compared to the same month last year," or "Did we meet our goal of a ten-percent increase in holiday sales?"

We define data mining as "the data-driven discovery and modeling of hidden patterns in large volumes of data." Data mining differs from the retrospective technologies above because it produces models - models that capture and represent the hidden patterns in the data. With it, a user can discover patterns and build models automatically, without knowing exactly what she's looking for. The models are both descriptive and prospective. They address why things happened and what is likely to happen next. A user can pose "what-if" questions to a data-mining model that can not be queried directly from the database or warehouse. Examples include: "What is the expected lifetime value of every customer account," "Which customers are likely to open a money market account," or "Will this customer cancel our service if we introduce fees?"

The information technologies associated with DM are neural networks, genetic algorithms, fuzzy logic, and rule induction. It is outside the scope of this article to elaborate on all of these technologies. Instead, we will focus on business needs and how data mining solutions for these needs can translate into dollars.

Mapping Business Needs to Solutions and Profits

What can data mining do for your organization? In the introduction, we described several strategic opportunities for an organization to use data for advantage: business expansion, profitability, cost reduction, and sales and marketing. Let's consider these opportunities very concretely through several examples where companies successfully applied DM.

Expanding your business: Keystone Financial of Williamsport, PA, wanted to expand their customer base and attract new accounts through a LoanCheck offer. To initiate a loan, a recipient just had to go to a Keystone branch and cash the LoanCheck. Keystone introduced the $5000 LoanCheck by mailing a promotion to existing customers.

The Keystone database tracks about 300 characteristics for each customer. These characteristics include whether the person had already opened loans in the past two years, the number of active credit cards, the balance levels on those cards, and finally whether or not they responded to the $5000 LoanCheck offer. Keystone used data mining to sift through the 300 customer characteristics, find the most significant ones, and build a model of response to the LoanCheck offer. Then, they applied the model to a list of 400,000 prospects obtained from a credit bureau.

By selectively mailing to the best-rated prospects determined by the DM model, Keystone generated $1.6M in additional net income from 12,000 new customers.

Reducing costs: Empire Blue Cross/Blue Shield is New York State's largest health insurer. To compete with other healthcare companies, Empire must provide quality service and minimize costs. Attacking costs in the form of fraud and abuse is a cornerstone of Empire's strategy, and it requires considerable investigative skill as well as sophisticated information technology.

The latter includes a data mining application that profiles each physician in the Empire network based on patient claim records in their database. From the profile, the application detects subtle deviations in physician behavior relative to her/his peer group. These deviations are reported to fraud investigators as a "suspicion index." A physician who performs a high number of procedures per visit, charges 40% more per patient, or sees many patients on the weekend would be flagged immediately from the suspicion index score.

What has this DM effort returned to Empire? In the first three years, they realized fraud-and-abuse savings of $29M, $36M, and $39M respectively.

Improving sales effectiveness and profitability: Pharmaceutical sales representatives have a broad assortment of tools for promoting products to physicians. These tools include clinical literature, product samples, dinner meetings, teleconferences, golf outings, and more. Knowing which promotions will be most effective with which doctors is extremely valuable since wrong decisions can cost the company hundreds of dollars for the sales call and even more in lost revenue.

The reps for a large pharmaceutical company collectively make tens of thousands of sales calls. One drug maker linked six months of promotional activity with corresponding sales figures in a database, which they then used to build a predictive model for each doctor. The data-mining models revealed, for instance, that among six different promotional alternatives, only two had a significant impact on the prescribing behavior of physicians. Using all the knowledge embedded in the data-mining models, the promotional mix for each doctor was customized to maximize ROI.

Although this new program was rolled out just recently, early responses indicate that the drug maker will exceed the $1.4M sales increase originally projected. Given that this increase is generated with no new promotional spending, profits are expected to increase by a similar amount.

Looking back at this set of examples, we must ask, "Why was data mining necessary?" For Keystone, response to the loan offer did not exist in the new credit bureau database of 400,000 potential customers. The model predicted the response given the other available customer characteristics. For Empire, the suspicion index quantified the differences between physician practices and peer (model) behavior. Appropriate physician behavior was a multi-variable aggregate produced by data mining - once again, not available in the database. For the drug maker, the promotion and sales databases contained the historical record of activity. An automated data mining method was necessary to model each doctor and determine the best combination of promotions to increase future sales.

Getting Started

In each case presented above, data mining yielded significant benefits to the business. Some were top-line results that increased revenues or expanded the customer base. Others were bottom-line improvements resulting from cost-savings and enhanced productivity. The natural next question is, "How can my organization get started and begin to realize the competitive advantages of DM?"

In our experience, pilot projects are the most successful vehicles for introducing data mining. A pilot project is a short, well-planned effort to bring DM into an organization. Good pilot projects focus on one very specific business need, and they involve business users up front and throughout the project. The duration of a typical pilot project is one to three months, and it generally requires 4 to 10 people part-time.

The role of the executive in such pilot projects is two-pronged. At the outset, the executive participates in setting the strategic goals and objectives for the project. During the project and prior to roll out, the executive takes part by supervising the measurement and evaluation of results. Lack of executive sponsorship and failure to involve business users are two primary reasons DM initiatives stall or fall short.

In reading this article, perhaps you've developed a vision and want to proceed - to address a pressing business problem by sponsoring a data mining pilot project. Twisting the old adage, we say "just because you should doesn't mean you can." Be aware that a capability assessment needs to be an integral component of a DM pilot project. The assessment takes a critical look at data and data access, personnel and their skills, equipment, and software. Organizations typically underestimate the impact of data mining (and information technology in general) on their people, their processes, and their corporate culture. The pilot project provides a relatively high-reward, low-cost, and low-risk opportunity to quantify the potential impact of DM.

Another stumbling block for an organization is deciding to defer any data mining activity until a data warehouse is built. Our experience indicates that, oftentimes, DM could and should come first. The purpose of the data warehouse is to provide users the opportunity to study customer and market behavior both retrospectively and prospectively. A data mining pilot project can provide important insight into the fields and aggregates that need to be designed into the warehouse to make it really valuable. Further, the cost savings or revenue generation provided by DM can provide bootstrap funding for a data warehouse or related initiatives.

Recapping, in this article we addressed the key questions executives have about data mining - what it is, what the benefits are, and how to get started. Armed with this knowledge, begin with a pilot project. From there, you can continue building the data mining capability in your organization; to expand your business, improve profitability, reduce costs, and market your products more effectively.


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Data Mining: Its Description and Uses

Data mining also known as the process of analyzing the KDD which stands for Knowledge Discovery in Databases is a part of statistics and computer science. It is a process which aims to find out many various patterns in enormous sets of relational data.

It uses ways at the fields of machine learning, database systems, artificial intelligence, and statistics. It permits users to examine data from many various perspectives, sort it, and summarize the identified relationships.

In general, the objective of data mining process is to obtain info out of a data set and convert it into a comprehensible outline. Also, it includes the following: data processing, data management and database aspects, visualization, complexity considerations, online updating, inference and model considerations, and interestingness metrics.

On the other hand, the actual data mining assignment is the semi-automatic or automatic exploration of huge quantities of information to extract patterns that are interesting and previously unknown. Such patterns can be the unusual records or the anomaly detection, data records groups or the cluster analysis, and the dependencies or the association rule mining. Usually, this involves utilizing database methods like spatial indexes. Such patters could be perceived as a type of summary of input data, and could be used in further examination or, for example, in predictive analysis and machine learning.

Today, data mining is utilized by different consumer-focused companies like those in the financial, retails, marketing, and communications fields. It permits such companies to find out relationships among the internal aspects like staff skills, price, product positioning, and external aspects like customer information, competition, and economic indicators. Additionally, it allows them to define the effect on corporate profits, sales, and customer satisfaction; and dig into the summary information to be able to see transactional data in detail.

With data mining process, a retailer can make use of point-of-scale customer purchases records to send promotions based on the purchase history of a client. The retailer can improve products and campaigns or promotions that can be appealing to a definite customer group by using mining data from comment cards.

Generally, any of the following relationships are obtained.

1. Associations: Data could be mined to recognize associations.
2. Clusters: Data are sorted based on a rational relationships or consumer preferences.
3. Sequential Patters: Data is mined to expect patterns and trends in behavior.
4. Classes: Data that are stored are utilized to trace data in predetermined segments.


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Data Entry Services For Multinational Companies

Data entry services envelop most multinational companies and specialized trades, which include data conversion, text and image processing, catalog processing, image enrichment, image bowdlerization, and image manipulation. Many organizations gather such information through handwritten proceedings or non transferable records of some nature, however others use full automation technical method to capture and deal with the information. For the former corporate, data entry transactions such as overhead expense hours, accounting entries or expenditure checks are items that work exceptionally fine for the dealings to be entered one at a time into an accounting software package. After being entered, the software generally manipulates the data into the accurate reports.

In earlier times, outsourcing was considered to be as a transistor alternative of meeting particular intentions; it is at present fetching the top commerce option. Viewed as a temporary business resolution, outsourcing is now a tactically imperative corporate verdict. Outsourcing your services will reduce your expenditures with improved services. Getting the profits of outsourcing data entry services for your business will be a wise preference. Numerous offshore corporations guarantee speedy and accurate data entry services.

These corporations offer entry solutions from trade specialist professionals and flexibility as per user necessities. All new reports say, development of outsourcing small priority work will persist to get bigger gradually. For those genuinely interested in creating a person on the World Wide Web by managing their data entry effectively, it is best recommended that they seek the aid of a well established professional or firm which will be well capable of delivering the best of results in a formidable manner. There are a number of data entry experts around which can help webmasters take care of their requirements, however opting for the ideal one can become a difficult task. It is therefore essential to lookout for those which have a number of positive reviews accredited to their name.



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Data Entry Services Are The Core of Any Business

Data entry is the core of any business and though it may appear to be easy to manage and handle, this involves many processes that need to be dealt systematically. Huge changes have taken place in the field of data entry and due to this handling the work has become much easier then before. So if you want to make use of the best data entry services to maintain the data and other information about your company, you must be ready to spend money for this. It is in no way an attempt to say that data entry services are costly, but just to say that good services will not come that cheap either. You just need to decide if you will hire professionals to do this work in house or if you would like to hire the services from an outside firm. The business is your and you are the best person to decide what is suitable for your business.

Doing the data entry of any business in house can be advantageous and disadvantageous as well. The main advantage can be in the form that you can keep an eye on the work being done to maintain proper records of all aspects of your company. This can prove to be a bit costly to you as you will have to hire the services of a data entry operator. The employee will be on rolls and thus will be entitled to all the benefits like allowances and other bonuses. So another option that you can use for this is to get a third party handle the work for you. This is a better option as you can hire the services depending on the type of work you need to be done.

This is one of the core components of your business and consequently you must ensure that this is handled properly. Data entry services are not the only aspect that business owners are seeking out these days. With the huge surge in the field of information and technology data conversion is equally important. The need to convert the data that has been entered is gaining momentum day by day. Conversion of the data makes it more accessible and this can be used easily without too many hassles to draw customers for buying the goods. Traditional methods have been done away with and professionals who work for data entry services these days are highly skilled and in tune with the latest methods.

Data entry services done for a company by third party has been found to be very suitable. In fact studies have indicated that outsourcing data entry services is one the rise due to the high rate of success enjoyed by business owners for this. The main advantage of getting data entry services done by a third party is that it works out very cheap and the work done is of the top most quality. So if the data entry services of the best quality id provided there is absolutely no chance why someone would not undertake the process to increase and brighten business prospects.


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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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Unleash the Hidden Potential of Your Business Data With Data Mining and Extraction Services

Every business, small or large, is continuously amassing data about customers, employees and nearly every process in their business cycle. Although all management staff utilize data collected from their business as a basis for decision making in areas such as marketing, forecasting, planning and trouble-shooting, very often they are just barely scratching the surface. Manual data analysis is time-consuming and error-prone, and its limited functions result in the overlooking of valuable information that improve bottom-lines. Often, the sheer quantity of data prevents accurate and useful analysis by those without the necessary technology and experience. It is an unfortunate reality that much of this data goes to waste and companies often never realize that a valuable resource is being left untapped.

Automated data mining services allow your company to tap into the latent potential of large volumes of raw data and convert it into information that can be used in decision-making. While the use of the latest software makes data mining and data extraction fast and affordable, experienced professional data analysts are a key part of the data mining services offered by our company. Making the most of your data involves more than automatically generated reports from statistical software. It takes analysis and interpretation skills that can only be performed by experienced data analysis experts to ensure that your business databases are translated into information that you can easily comprehend and use in almost every aspect of your business.

Who Can Benefit From Data Mining Services?

If you are wondering what types of companies can benefit from data extraction services, the answer is virtually every type of business. This includes organizations dealing in customer service, sales and marketing, financial products, research and insurance.

How is Raw Data Converted to Useful Information?

There are several steps in data mining and extraction, but the most important thing for you as a business owner is to be assured that, throughout the process, the confidentiality of your data is our primary concern. Upon receiving your data, it is converted into the necessary format so that it can be entered into a data warehouse system. Next, it is compiled into a database, which is then sifted through by data mining experts to identify relevant data. Our trained and experienced staff then scan and analyze your data using a variety of methods to identify association or relationships between variables; clusters and classes, to identify correlations and groups within your data; and patterns, which allow trends to be identified and predictions to be made. Finally, the results are compiled in the form of written reports, visual data and spreadsheets, according to the needs of your business.

Our team of data mining, extraction and analyses experts have already helped a great number of businesses to tap into the potential of their raw data, with our speedy, cost-efficient and confidential services. Contact us today for more information on how our data mining and extraction services can help your business.


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Things You Should Know about Data Mining or Data Capturing

The World Wide Web is a portal containing billions of quality information, spanning resources from around the globe. Through the years, the internet has developed into a competitive business environment which offers advertising, promotions, sales and marketing innovations that has rapidly created a following with most websites, and gave birth to online business transactions and unprecedented financial growth.

Data mining comes into the picture in quite an obscure procedure. Most companies utilize data entry level workers to edit or create listings for the items they promote or sell online. Data mining is that early stage prior to the data entry work which utilizes available resources online to gather bits and pieces of information relevant to the business or website they are categorizing.

In a certain point of view, data mining holds a great deal of importance, as the primary keeper of the quality of the items being listed by the data entry personnel as filtered through the stages under data mining and data capturing.

As mentioned earlier, data mining is a very obscure procedure. The reason for my saying this is because of the fact that certain restrictions or policies are enforced by websites or business institutions particularly on the quality of data capturing, which may seem too time-consuming, meticulous and stringent.

These methodologies are but without explanation as well. As only the most qualified resources bearing the most relevant information can be posted online. Many data mining personnel can only produce satisfactory work on the data entry levels, after enhancing the quality of output from the data mining or data capturing stage.

Data mining includes two common strategies. The first one would be a strategy based on manual labor and data checking, with the use of online or local manual tools and scripts to gather the right information. The second would be through the use of web crawlers or robots to perform the task of checking for information on various websites automatically. The second stage offers a faster method for gathering and listing information.

But often-times the procedure spit out very garbled data, often confusing personnel more than helping.

Data mining is a highly exhaustive activity, often expending more effort, time and money than other types of work. Leveling them out, local data mining is a sure fire method to gain rapid listings of information, as collected by the information miners.


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Various Data Mining Techniques

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

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

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

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

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

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

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



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Data Management Services

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

Entering of data

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

EDC

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

Data changing

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

Managing data service

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

Data extraction and cleansing

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

Web scraping, data extraction services, web extraction, imaging, catalog conversion, web data mining and others are the other management services offered by data mining organization. If your business organization needs such services here is one that can be of great significance that is web scraping and data mining


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Accelerating Accumulated Data Mining

We all have heard of Data Mining and we have all seen the abilities it can produce, but we also know how tedious the collection of data can be. It is the same for a little small company with a few customers as it is for a large company with millions of customers. Additionally how do you keep your data safe?

We have all heard of Identity Theft and the importance of secure data. But just because we have spent millions of dollars in IT work does not mean we know it is accurate? Things change fast you see; people get new telephone numbers, change addresses and jobs at least one of the three every three years. The chances of any database having accurate information is simply not possible.

Thus if we are data mining we need a way to verify which data sets are accurate and believe it or not the last set of data may not be the most accurate therefore we cannot simply discard the old data for the new data you see? We need ways to accelerate the accumulated data so we can run through it as fast as possible yet we must insure that our data mining techniques are taking into consideration miss matched data and incorrect data, along with inaccurate data.

Data Mining may have been over hyped a little and those business systems or even government data mining systems at the NSA; if they do not take into consideration these thoughts they are basically worthless and should not be considered you see? Think on this in 2006.


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Why Web Scraping Software Won't Help

How to get continuous stream of data from these websites without getting stopped? Scraping logic depends upon the HTML sent out by the web server on page requests, if anything changes in the output, its most likely going to break your scraper setup.

If you are running a website which depends upon getting continuous updated data from some websites, it can be dangerous to reply on just a software.

Some of the challenges you should think:

1. Web masters keep changing their websites to be more user friendly and look better, in turn it breaks the delicate scraper data extraction logic.

2. IP address block: If you continuously keep scraping from a website from your office, your IP is going to get blocked by the "security guards" one day.

3. Websites are increasingly using better ways to send data, Ajax, client side web service calls etc. Making it increasingly harder to scrap data off from these websites. Unless you are an expert in programing, you will not be able to get the data out.

4. Think of a situation, where your newly setup website has started flourishing and suddenly the dream data feed that you used to get stops. In today's society of abundant resources, your users will switch to a service which is still serving them fresh data.

Getting over these challenges

Let experts help you, people who have been in this business for a long time and have been serving clients day in and out. They run their own servers which are there just to do one job, extract data. IP blocking is no issue for them as they can switch servers in minutes and get the scraping exercise back on track. Try this service and you will see what I mean here.



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Top 5 Online Data Entry Companies That Pay Good Cash

Online data entry jobs are ideal for anyone who wants some extra cash at the comfort of their home. Big companies outsource data entry work through data management service providers. These firms appoint workers to work from their home. Once the registration is over they provide data to enter online into their websites. This job pays very lucrative income for you. Irrespective of country, you can join these companies and make money from home.

Let me suggest few top companies that pay good cash for your work. These companies work for multinational corporate giants to complete the process of data management.

Click and work

Click and work is one of the good companies which provide various freelance data entry jobs. This company was started in year 2000 and has been providing jobs for qualified persons worldwide. They provide data entry typist jobs, analyst, web searchers, team leaders, writer jobs and many more. Thousands of people work for them from home and collect payments by check or PayPal.

Dion data solutions

This is a USA based data management company with high standards. They provide different kinds of data entry jobs and trainings with no cost to individuals and families. They accept application through emails. No phone calls can be made to them, because of the increased submission of applications. You should have a minimum type speed of 60 words per minute and a computer with internet connection to apply for positions.

Speak-write
This company offers various data typing jobs for experienced people. You should have minimum type speed and accuracy in assignment. They do not provide any jobs for learners and new people. However, if you have 65 words per minute typing speed you can apply for any data typist job. You can expect lucrative income from them.

Key for cash

Key for cash provides online typing works for everyone who needs extra income. They offer data which has to be typed on their website using log in password they provide. You do not need to pay a dime for joining them. You need no commitment either. You can earn as much as you want working as much as or as little as you wish. If you are 18 years old or more you can apply for online typist jobs.

Mulberry studio

Mulberry studio offers data entry transcription jobs in medical and general field. If you have a typing speed of 75 words per minute, you can give it a try to work for them. You should also have good command over English. Minimum experience in transcription and word processing would be desired by them. They pay you good working environment and lucrative income. They provide domestic and international data entry jobs which you can do from your home and make good money.


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Customer Relationship Management (CRM) Using Data Mining Services

In today's globalized marketplace Customer relationship management (CRM) is deemed as crucial business activity to compete efficiently and outdone the competition. CRM strategies heavily depend on how effectively you can use the customer information in meeting their needs and expectations which in turn leads to more profit.

Some basic questions include - what are their specific needs, how satisfied they are with your product or services, is there a scope of improvement in existing product/service and so on. For better CRM strategy you need a predictive data mining models fueled by right data and analysis. Let me give you a basic idea on how you can use Data mining for your CRM objective.

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

Let me explain last three steps in detail.

Visualize a Model:
Building a predictive data model is an iterative process. You may require 2-3 models in order to discover the one that best suit your business problem. In searching a right data model you may need to go back, do some changes or even change your problem statement.

In building a model you start with customer data for which the result is already known. For example, you may have to do a test mailing to discover how many people will reply to your mail. You then divide this information into two groups. On the first group, you predict your desired model and apply this on remaining data. Once you finish the estimation and testing process you are left with a model that best suits your business idea.

Explore Model:
Accuracy is the key in evaluating your outcomes. For example, predictive models acquired through data mining may be clubbed with the insights of domain experts and can be used in a large project that can serve to various kinds of people. The way data mining is used in an application is decided by the nature of customer interaction. In most cases either customer contacts you or you contact them.

Set up Model & Start Monitoring:
To analyze customer interactions you need to consider factors like who originated the contact, whether it was direct or social media campaign, brand awareness of your company, etc. Then you select a sample of users to be contacted by applying the model to your existing customer database. In case of advertising campaigns you match the profiles of potential users discovered by your model to the profile of the users your campaign will reach.

In either case, if the input data involves income, age and gender demography, but the model demands gender-to-income or age-to-income ratio then you need to transform your existing database accordingly.


Source: http://ezinearticles.com/?Customer-Relationship-Management-%28CRM%29-Using-Data-Mining-Services&id=4641198

Data Mining for Dollars

The more you know, the more you're aware you could be saving. And the deeper you dig, the richer the reward.

That's today's data mining capsulation of your realization: awareness of cost-saving options amid logistical obligations.

According to global trade group Association for Information and Image Management (AIIM), fewer than 25% of organizations in North America and Europe are currently utilizing captured data as part of their business process. With high ease and low cost associated with utilization of their information, this unawareness is shocking. And costly.

Shippers - you're in prime position to benefit the most by data mining and assessing your electronically-captured billing records, by utilizing a freight bill processing provider, to realize and receive significant savings.

Whatever your volume, the more you know about your transportation options, throughout all modes, the easier it is to ship smarter and save. A freight bill processor is able to offer insight capable of saving you 5% - 15% annually on your transportation expenditures.

The University of California - Los Angeles states that data mining is the process of analyzing data from different perspectives and summarizing it into useful information - knowledge that can be used to increase revenue, cuts costs, or both. Data mining software is an analytical tool that allows investigation of data from many different dimensions, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations among dozens of fields in large relational databases. Practically, it leads you to noticeable shipping savings.

Data mining and subsequent reporting of shipping activity will yield discovery of timely, actionable information that empowers you to make the best logistics decisions based on carrier options, along with associated routes, rates and fees. This function also provides a deeper understanding of trends, opportunities, weaknesses and threats. Exploration of pertinent data, in any combination over any time period, enables you the operational and financial view of your functional flow, ultimately providing you significant cost savings.

With data mining, you can create a report based on a radius from a ship point, or identify opportunities for service or modal shifts, providing insight regarding carrier usage by lane, volume, average cost per pound, shipment size and service type. Performance can be measured based on overall shipping expenditures, variances from trends in costs, volumes and accessorial charges.

The easiest way to get into data mining of your transportation information is to form an alliance with a freight bill processor that provides this independent analytical tool, and utilize their unbiased technologies and related abilities to make shipping decisions that'll enable you to ship smarter and save.

Source: http://ezinearticles.com/?Data-Mining-for-Dollars&id=7061178

Has It Been Done Before? Optimize Your Patent Search Using Patent Scraping Technology

Has it been done before? Optimize your Patent Search using Patent Scraping Technology.

Since the US patent office opened in 1790, inventors across the United States have been submitting all sorts of great products and half-baked ideas to their database. Nowadays, many individuals get ideas for great products only to have the patent office do a patent search and tell them that their ideas have already been patented by someone else! Herin lies a question: How do I perform a patent search to find out if my invention has already been patented before I invest time and money into developing it?

The US patent office patent search database is available to anyone with internet access.

US Patent Search Homepage

Performing a patent search with the patent searching tools on the US Patent office webpage can prove to be a very time consuming process. For example, patent searching the database for "dog" and "food" yields 5745 patent search results. The straight-forward approach to investigating the patent search results for your particular idea is to go through all 5745 results one at a time looking for yours. Get some munchies and settle in, this could take a while! The patent search database sorts results by patent number instead of relevancy. This means that if your idea was recently patented, you will find it near the top but if it wasn't, you could be searching for quite a while. Also, most patent search results have images associated with them. Downloading and displaying these images over the internet can be very time consuming depending on you internet connection and the availability of the patent search database servers.

Because patent searches take such a long time, many companies and organizations are looking ways to improve the process. Some organizations and companies will hire employees for the sole purpose of performing patent searches for them. Others contract out the job to small business that specialize in patent searches. The latest technology for performing patent searches is called patent scraping.

Patent scraping is the process of writing computer automated scripts that analyze a website and copy only the content you are interested in into easily accessible databases or spreadsheets on your computer. Because it is a computerized script performing the patent search, you don't need a separate employee to get the data, you can let it run the patent scraping while you perform other important tasks! Patent scraping technology can also extract text content from images. By saving the images and textual content to your computer, you can then very efficiently search them for content and relevancy; thus saving you lots of time that could be better spent actually inventing something!

To put a real-world face on this, let us consider the pharmaceutical industry. Many different companies are competing for the patent on the next big drug. It has become an indispensible tactic of the industry for one company to perform patent searches for what patents the other companies are applying for, thus learning in which direction the research and development team of the other company is taking them. Using this information, the company can then choose to either pursue that direction heavily, or spin off in a different direction. It would quickly become very costly to maintain a team of researchers dedicated to only performing patent searches all day. Patent scraping technology is the means for figuring out what ideas and technologies are coming about before they make headline news. It is by utilizing patent scraping technology that the large companies stay up to date on the latest trends in technology.

While some companies choose to hire their own programming team to do their patent scraping scripts for them, it is much more cost effective to contract out the job to a qualified team of programmers dedicated to performing such services.


Source: http://ezinearticles.com/?Has-It-Been-Done-Before?-Optimize-Your-Patent-Search-Using-Patent-Scraping-Technology&id=171000

Advantages of Online Data Entry Services

People all over the world are enthusiastic to buy online data entry services as they find it cost effective. Most of them have an impression that they get quality services against the prices they have to pay. Entering data online is of a great help to business units of all sizes as they consider them as their main basis of profession.

Online data entering and typing services providers have skilled resources at their service who deliver quality work timely. These service providers have modernized technology, assuring cent percent security of data. Online data entry services include the following:

    Data entry
    Data Processing
    Product entry
    Data typing
    Data mining, Data capture/collection
    Business Process Outsourcing
    Data Conversion
    Form Filling
    Web and mortgage research
    Extraction services
    Online copying, pasting, editing, sorting, as well as indexing data
    E-books and e-magazines data entry

Get companies world wide quality services to business units of all sizes, some of the common input formats are:

    PDF
    TIFF
    GIF
    XBM
    JPG
    PNG
    BMP
    TGA
    XML
    HTML
    SGML
    Printed documents
    Hard copies, etc

Benefits of outsourcing online data entering services:

Major benefits of data entry for business units is that they get the facts and figures which helps in taking strategic decisions for the organization. The data projected by numbers turns to be a factor of evaluation that accelerates the progress of the business. Online data typing services maintain high level of security by using systems that are highly protected.

The business organization progresses because of right decisions taken with the help of superior quality data available.

    Save operational overhead expense.
    Saves time and space.
    Accurate services can be accessed.
    Eliminating the paper documents.
    Cost effective.
    Data accessible from anywhere in the world.
    100% work satisfaction.
    Access to professional and experienced data typing services.
    Adequate knowledge of wide range industrial needs.
    Use of highly advance technologies for quality results.

Business organizations find themselves blessed because of the benefits they receive out of outsourcing their projects on online data entering and typing services, because it not only saves their time but also saves a huge amount of money.

Upcoming business companies can focus on their key business functions instead of dealing with non-key business activities. They find it sensible to outsource their confidential and crucial projects to trustworthy online data entry services and remain free for their key business activities. These companies have several layers of quality control which assures 99.9% quality on projects on online data entry.



Source: http://ezinearticles.com/?Advantages-of-Online-Data-Entry-Services&id=6526483