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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Data Mining and Financial Data Analysis

Most marketers understand the value of collecting financial data, but also realize the challenges of leveraging this knowledge to create intelligent, proactive pathways back to the customer. Data mining - technologies and techniques for recognizing and tracking patterns within data - helps businesses sift through layers of seemingly unrelated data for meaningful relationships, where they can anticipate, rather than simply react to, customer needs as well as financial need. In this accessible introduction, we provides a business and technological overview of data mining and outlines how, along with sound business processes and complementary technologies, data mining can reinforce and redefine for financial analysis.

Objective:

1. The main objective of mining techniques is to discuss how customized data mining tools should be developed for financial data analysis.

2. Usage pattern, in terms of the purpose can be categories as per the need for financial analysis.

3. Develop a tool for financial analysis through data mining techniques.

Data mining:

Data mining is the procedure for extracting or mining knowledge for the large quantity of data or we can say data mining is "knowledge mining for data" or also we can say Knowledge Discovery in Database (KDD). Means data mining is : data collection , database creation, data management, data analysis and understanding.

There are some steps in the process of knowledge discovery in database, such as

1. Data cleaning. (To remove nose and inconsistent data)

2. Data integration. (Where multiple data source may be combined.)

3. Data selection. (Where data relevant to the analysis task are retrieved from the database.)

4. Data transformation. (Where data are transformed or consolidated into forms appropriate for mining by performing summary or aggregation operations, for instance)

5. Data mining. (An essential process where intelligent methods are applied in order to extract data patterns.)

6. Pattern evaluation. (To identify the truly interesting patterns representing knowledge based on some interesting measures.)

7. Knowledge presentation.(Where visualization and knowledge representation techniques are used to present the mined knowledge to the user.)

Data Warehouse:

A data warehouse is a repository of information collected from multiple sources, stored under a unified schema and which usually resides at a single site.

Text:

Most of the banks and financial institutions offer a wide verity of banking services such as checking, savings, business and individual customer transactions, credit and investment services like mutual funds etc. Some also offer insurance services and stock investment services.

There are different types of analysis available, but in this case we want to give one analysis known as "Evolution Analysis".

Data evolution analysis is used for the object whose behavior changes over time. Although this may include characterization, discrimination, association, classification, or clustering of time related data, means we can say this evolution analysis is done through the time series data analysis, sequence or periodicity pattern matching and similarity based data analysis.

Data collect from banking and financial sectors are often relatively complete, reliable and high quality, which gives the facility for analysis and data mining. Here we discuss few cases such as,

Eg, 1. Suppose we have stock market data of the last few years available. And we would like to invest in shares of best companies. A data mining study of stock exchange data may identify stock evolution regularities for overall stocks and for the stocks of particular companies. Such regularities may help predict future trends in stock market prices, contributing our decision making regarding stock investments.

Eg, 2. One may like to view the debt and revenue change by month, by region and by other factors along with minimum, maximum, total, average, and other statistical information. Data ware houses, give the facility for comparative analysis and outlier analysis all are play important roles in financial data analysis and mining.

Eg, 3. Loan payment prediction and customer credit analysis are critical to the business of the bank. There are many factors can strongly influence loan payment performance and customer credit rating. Data mining may help identify important factors and eliminate irrelevant one.

Factors related to the risk of loan payments like term of the loan, debt ratio, payment to income ratio, credit history and many more. The banks than decide whose profile shows relatively low risks according to the critical factor analysis.

We can perform the task faster and create a more sophisticated presentation with financial analysis software. These products condense complex data analyses into easy-to-understand graphic presentations. And there's a bonus: Such software can vault our practice to a more advanced business consulting level and help we attract new clients.

To help us find a program that best fits our needs-and our budget-we examined some of the leading packages that represent, by vendors' estimates, more than 90% of the market. Although all the packages are marketed as financial analysis software, they don't all perform every function needed for full-spectrum analyses. It should allow us to provide a unique service to clients.

The Products:

ACCPAC CFO (Comprehensive Financial Optimizer) is designed for small and medium-size enterprises and can help make business-planning decisions by modeling the impact of various options. This is accomplished by demonstrating the what-if outcomes of small changes. A roll forward feature prepares budgets or forecast reports in minutes. The program also generates a financial scorecard of key financial information and indicators.

Customized Financial Analysis by BizBench provides financial benchmarking to determine how a company compares to others in its industry by using the Risk Management Association (RMA) database. It also highlights key ratios that need improvement and year-to-year trend analysis. A unique function, Back Calculation, calculates the profit targets or the appropriate asset base to support existing sales and profitability. Its DuPont Model Analysis demonstrates how each ratio affects return on equity.

Financial Analysis CS reviews and compares a client's financial position with business peers or industry standards. It also can compare multiple locations of a single business to determine which are most profitable. Users who subscribe to the RMA option can integrate with Financial Analysis CS, which then lets them provide aggregated financial indicators of peers or industry standards, showing clients how their businesses compare.

iLumen regularly collects a client's financial information to provide ongoing analysis. It also provides benchmarking information, comparing the client's financial performance with industry peers. The system is Web-based and can monitor a client's performance on a monthly, quarterly and annual basis. The network can upload a trial balance file directly from any accounting software program and provide charts, graphs and ratios that demonstrate a company's performance for the period. Analysis tools are viewed through customized dashboards.

PlanGuru by New Horizon Technologies can generate client-ready integrated balance sheets, income statements and cash-flow statements. The program includes tools for analyzing data, making projections, forecasting and budgeting. It also supports multiple resulting scenarios. The system can calculate up to 21 financial ratios as well as the breakeven point. PlanGuru uses a spreadsheet-style interface and wizards that guide users through data entry. It can import from Excel, QuickBooks, Peachtree and plain text files. It comes in professional and consultant editions. An add-on, called the Business Analyzer, calculates benchmarks.

ProfitCents by Sageworks is Web-based, so it requires no software or updates. It integrates with QuickBooks, CCH, Caseware, Creative Solutions and Best Software applications. It also provides a wide variety of businesses analyses for nonprofits and sole proprietorships. The company offers free consulting, training and customer support. It's also available in Spanish.



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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.



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Data Mining Is Useful for Business Application and Market Research Services

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

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

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

Benefits of Data mining services in Business

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

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

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




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Healthcare Marketing Series - Data Mining - The 21st Century Marketing Gold Rush

There is gold in them there hills! Well there is gold right within a few blocks of your office. Mining for patients, not unlike mining for gold or drilling for oil requires either great luck or great research.

It's all about the odds.

It's true that like old Jed from the Beverly Hillbillies, you might just take a shot and strike oil. But more likely you might drill a dry hole or dig a mine and find dirt not diamonds. Without research you might be a mere 2 feet from pay dirt, but drilling or mining in just the wrong spot.

Now oil companies and gold mining companies spend millions, if not, billions of dollars studying where and how to effectively find the "mother load". If market research is good enough for the big boys, it should be good enough for the healthcare provider. Remember as a health care professional you probably don't have the extras millions laying around to squander on trial and error marketing.

If you did there would be little need for you to market to find new patients to help.

In previous articles in the Health Care Marketing Series we talked about developing a marketing strategy, using metrics to measure the performance of your marketing execution, developing effective marketing warheads based on your marketing strategy, evaluating the most efficient ways to deliver those warheads, your marketing missile systems, and tying several marketing methods together into a marketing MIRV.

If you have been following along with our articles and starting to integrate the concepts detailed in them, by now you should have an excellent marketing infrastructure. Ready to launch laser guided marketing missiles tipped with nuclear marketing MIRVs. The better you have done your research, the more detailed your marketing strategy, the more effective and efficient your delivery systems, the bigger bang you'll receive from your marketing campaign. And ultimately the more lives you will help to change of patients that truly can benefit from your skills and talents as a doctor.

Sounds like you're ready for healthcare marketing shock and awe.

Everything is ready to launch, this is great, press the button and fire away!

Ah, but wait just a minute, General. What is the target? Where are they? What are the aiming coordinates?

The target? Why of course all those sick people out there.

Where are they? Well of course, out there!

The coordinates? Man just press the button, carpet bomb man. Carpet bomb!

This scenario is designed to show you how quickly the wheels can come off even the best intended marketing war machine. It brings us back full circle. We are right back to our original article on marketing strategy.

But this time we are going to introduce the concept of data mining. If you remember, our article on marketing strategy talked about doing research. We talked about research as the true cornerstone of all marketing efforts.

What is the target, General?

Answering this question is a little difficult and the truth is each healthcare provider needs to determine his or her high value target. And more importantly needs to know how to determine his or her high value targets.

Let's go back to our launch scenario to illustrate this point. Let's continue with our military analogy. Let's say we have several aircraft carriers, a few destroyers and a fleet of rowboats, making up our marketing battlefield.

As we have discussed previously, waging a marketing war, like any war, consumes resources. So do we want to launch our nuclear marketing MIRVs, the most valuable resources in our arsenal, and target the fleet of rowboats?

Or would it be wiser to target those aircraft carriers?

Well the obvious answer is "get those carriers".

But here is where things get a little tricky. One man's aircraft carrier is another man's rowboat.

You have to data mine your practice to determine which targets are high value targets.

What goes into that data mining process? Well first and foremost, what conditions do you 1.like to treat, 2. have a proven track record of treating and 3. obtain a reasonable reimbursement for treating.

In my own practice, I typically do not like or enjoy treating shoulder problems. I don't know if I don't like treating shoulders because I haven't had great results with them or if I haven't had great results, because I don't like treating them. Needless to say my reimbursement for treating shoulder cases is relatively low.

So do I really want to carpet bomb my marketing terrain and come up with 10 new cases of rotator cuff tears? These cases, for more than one reason, are my rowboats.

On the contrary, I like to treat neurological conditions like chronic pain; Neuropathy patients, Spinal Stenosis patients, Tinnitus patients, patients with Parkinson's Disease and Multiple Sclerosis patients. I've had results with these types of cases that have been good enough to publish. Because they are complex and difficult cases, I obtain a better than average reimbursement for my efforts. These cases are my aircraft carriers. If my marketing campaign brings me ten cases with these types of problems, chances are that the patient will obtain some great relief, I will find working with them an intellectual and stimulating challenge and my marketing efforts will bring me a handsome return on investment.

So the first lesson of data mining is to identify your aircraft carriers. They must be "your" aircraft carriers. You must have a good personal track record of helping these types of patients. You should enjoy treating these types of cases. And you should be rewarded for your time and expertise.

That's the first step in the process. Identifying your high value targets. The next step is THE most important aspect of healthcare marketing. As I discussed above, I enjoy working with complex neurological cases. But how many of these types of patients exist in my marketing terrain and are they looking for the type of help I can offer?

Being able to accurately answer these important questions is the single most valuable information I can extract using data mining.

It doesn't matter if I like treating these cases. It doesn't matter if I make a good living treating these cases. It doesn't matter if my success in treating these cases has made the local news. What matters is 1. do these types of cases exist in my neighborhood and 2. are they looking for the help I can provide to them?

You absolutely positively need to know who is looking for what in your marketing terrain and if what people are clamoring for is what you have to offer.

This knowledge is the most powerful tool in your marketing arsenal. It's your secret weapon. It is the foundation of your marketing strategy. It is so important that you should consider moving your office if the results of your data mining don't reveal an ocean full of aircraft carriers in your marketing terrain for you to target.

If your market research does not reveal an abundance of aircraft carriers on your horizon, you need to either 1. move to a new battlefield, 2. re-target your efforts towards the destroyers in your market or 3. try to create a market.

Let's look at your last choice. Trying to create a market. Unless you are Coke or Pepsi, your ability to create a market as a health care provider is extremely limited. To continue on with our analogy, to create a market requires converting rowboats into, at least, destroyers, but better yet aircraft carriers.

What would it cost if you took a rowboat to a ship yard and told them to rebuild it as an aircraft carrier?

This is what you face if you try to create a market where none exists. Unless you have a personality flaw and thrive on selling ice to Eskimos, creating a market is not a rewarding proposition.

So scratch this option off the table right now.

What about re-targeting your campaign towards destroyers? That's a viable option. It's a good option. It's probably your best option. It's an option that will likely give you your best return on investment. It is recommended that you focus your arsenal on the destroyers while at the same time never passing on an opportunity to sink an aircraft carrier.

So what is the secret? How do you data mine for aircraft carriers?

Well its quite simple in the internet age. Just use the services of a market research firm. I like http://www.marketresearch.com They will do the data mining for you.

They can provide market intelligence that will tell you not only what the health care aircraft carriers are, but also where they are.

With this information, you will have a competitive advantage in your marketing battlefield. You can segment, and target high value targets in your area while your competitors squander their marketing resources on rowboats. Or even worse carpet bomb and hit ocean water, not valuable targets.

Your marketing strategy should be highly targeted. Your marketing resources should be well spent. As we discussed in our very first article on true "Marketing Strategy" you should enter the battle against your competition already knowing your have won.

What gives you this dominant position in the market, is knowing ahead-of-time, who is looking for what in your marketing terrain. In other words, not trying to create a market, but rather identifying existing market niches, specifically targeting them with laser guided precision and having headlines and ad copy based on your strength versus the weakness of your competition within that niche.

This research-based marketing strategy is sure to cause a big bang with potential patients.

And leave your competition trying to sell ice to Eskimos.

I hope you see how important market research is and why it is a good thing to spend some of your marketing budget on research before you waste your marketing resources on poorly targeted low value or no-value targets. This article was intended to give you a glimpse at how to use data mining and consumer demographics information as a foundation for the development of a scientific research-based marketing strategy. This article shows you how to use existing resources to give your marketing efforts (and you) a competitive advantage.



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Beneficial Data Collection Services

Internet is becoming the biggest source for information gathering. Varieties of search engines are available over the World Wide Web which helps in searching any kind of information easily and quickly. Every business needs relevant data for their decision making for which market research plays a crucial role. One of the services booming very fast is the data collection services. This data mining service helps in gathering relevant data which is hugely needed for your business or personal use.

Traditionally, data collection has been done manually which is not very feasible in case of bulk data requirement. Although people still use manual copying and pasting of data from Web pages or download a complete Web site which is shear wastage of time and effort. Instead, a more reliable and convenient method is automated data collection technique. There is a web scraping techniques that crawls through thousands of web pages for the specified topic and simultaneously incorporates this information into a database, XML file, CSV file, or other custom format for future reference. Few of the most commonly used web data extraction processes are websites which provide you information about the competitor's pricing and featured data; spider is a government portal that helps in extracting the names of citizens for an investigation; websites which have variety of downloadable images.

Aside, there is a more sophisticated method of automated data collection service. Here, you can easily scrape the web site information on daily basis automatically. This method greatly helps you in discovering the latest market trends, customer behavior and the future trends. Few of the major examples of automated data collection solutions are price monitoring information; collection of data of various financial institutions on a daily basis; verification of different reports on a constant basis and use them for taking better and progressive business decisions.

While using these service make sure you use the right procedure. Like when you are retrieving data download it in a spreadsheet so that the analysts can do the comparison and analysis properly. This will also help in getting accurate results in a faster and more refined manner.



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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.



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Basics of Online Web Research, Web Mining & Data Extraction Services

The evolution of the World Wide Web and Search engines has brought the abundant and ever growing pile of data and information on our finger tips. It has now become a popular and important resource for doing information research and analysis.

Today, Web research services are becoming more and more complicated. It involves various factors such as business intelligence and web interaction to deliver desired results.

Web Researchers can retrieve web data using search engines (keyword queries) or browsing specific web resources. However, these methods are not effective. Keyword search gives a large chunk of irrelevant data. Since each webpage contains several outbound links it is difficult to extract data by browsing too.

Web mining is classified into web content mining, web usage mining and web structure mining. Content mining focuses on the search and retrieval of information from web. Usage mining extract and analyzes user behavior. Structure mining deals with the structure of hyperlinks.

Web mining services can be divided into three subtasks:

Information Retrieval (IR): The purpose of this subtask is to automatically find all relevant information and filter out irrelevant ones. It uses various Search engines such as Google, Yahoo, MSN, etc and other resources to find the required information.

Generalization: The goal of this subtask is to explore users' interest using data extraction methods such as clustering and association rules. Since web data are dynamic and inaccurate, it is difficult to apply traditional data mining techniques directly on the raw data.

Data Validation (DV): It tries to uncover knowledge from the data provided by former tasks. Researcher can test various models, simulate them and finally validate given web information for consistency.



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Data Mining As a Process

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

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

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

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

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

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

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



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Is Web Scraping Relevant in Today's Business World?

Different techniques and processes have been created and developed over time to collect and analyze data. Web scraping is one of the processes that have hit the business market recently. It is a great process that offers businesses with vast amounts of data from different sources such as websites and databases.

It is good to clear the air and let people know that data scraping is legal process. The main reason is in this case is because the information or data is already available in the internet. It is important to know that it is not a process of stealing information but rather a process of collecting reliable information. Most people have regarded the technique as unsavory behavior. Their main basis of argument is that with time the process will be over flooded and therefore lead to parity in plagiarism.

We can therefore simply define web scraping as a process of collecting data from a wide variety of different websites and databases. The process can be achieved either manually or by the use of software. The rise of data mining companies has led to more use of the web extraction and web crawling process. Other main functions such companies are to process and analyze the data harvested. One of the important aspects about these companies is that they employ experts. The experts are aware of the viable keywords and also the kind of information which can create usable statistic and also the pages that are worth the effort. Therefore the role of data mining companies is not limited to mining of data but also help their clients be able to identify the various relationships and also build the models.

Some of the common methods of web scraping used include web crawling, text gripping, DOM parsing, and expression matching. The latter process can only be achieved through parsers, HTML pages or even semantic annotation. Therefore there are many different ways of scraping the data but most importantly they work towards the same goal. The main objective of using web scraping service is to retrieve and also compile data contained in databases and websites. This is a must process for a business to remain relevant in the business world.

The main questions asked about web scraping touch on relevance. Is the process relevant in the business world? The answer to this question is yes. The fact that it is employed by large companies in the world and has derived many rewards says it all. It is important to note that many people regarded this technology as a plagiarism tool and others consider it as a useful tool that harvests the data required for the business success.

Using of web scraping process to extract data from the internet for competition analysis is highly recommended. If this is the case, then you must be sure to spot any pattern or trend that can work in a given market.



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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



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Advantageous Data Entry Services in Era of Globalization

Data generally represent the information and can be defined with numbers or alphabetical symbols. Data entry can be determined as process that converts data from one form to another one. Such solutions usually includes almost all business fields and professional services, such as data conversion, offline data entry work, data processing, image processing, data entry outsourcing, data mining etc. One has to collect data on various topics and have to represent them in some meaningful manner.

There are several tasks for data entry services. It may includes data-entry into websites, tracking debit or credit card transactions, entry into electronic books, image formatting, keeping hard copy of office applications for scanning or printing, database for mails, use of data entry software as well as management of all these activities. In addition some time consuming tasks such as entering data in offline mode to track websites, gathering effective websites, which may need for consultation and to fill online forms. One of the good examples of data entry tasks is writing the image. You have to enter the images to incorporate pictures and attachments in magazines, e Books and white papers. Scanned images also needed to enter the details on the file. Another example of data-entry work is insurance claim. Insurance firms file a claim for insurance in process to get the cost of services. All systems for payment, form processing and insurance claims are followed by data entry services.

Data processing is also very useful tasks needed to be managed, regardless of company size or complexity. You have to follow some methods in order to accomplish your data processing tasks accurately. Such services help firms in terms of clear analysis of activities, policies, strategies and actions. Data processing and other services like data cleaning, image processing, OCR clean up, survey processing are related to provide a well-processed and complete data which can be used to get simple explanation of data.

There are plenty of advantages such services. For example data conversion is process which is very significant for any firm to drive their business powerfully. Data conversion can be considered as transfer of data from one format to another. There are also some other useful services like data transformation and many other which directly or indirectly essential for smooth functionality of any business.

Be advantageous in this competitive environment by choosing the right business services for benefits of yours and your organization.



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Benefits of Online Data Entry

There is no doubt that data entry is a vital part of business development because no organized activity can take place without the organized manipulation of data. But, even though the correct manipulation of data is at the heart of any enterprise, it is also true that this is an activity that is time consuming and repetitive. In the past, businesses had to dedicate a good portion of their work hours for the mind-numbing job of feeding data. However, with the arrival of the internet, there have been revolutionary changes in the way business handle data.

These days, a good volume of data entry work is being carried out online. Many companies, regardless of their size, are outsourcing this kind of work. This is more so in developed countries like the US, UK and Europe. These countries outsource such work to a pool of educated youth working from developing nations like China, India and Malaysia. The Internet is what makes this possible. Since the job is being done in a different country where currency rates are relatively low, the parent company is able to cut costs. More importantly, many companies have begun to realize that the time and effort they are putting into data entry could be routed to processes that will help the business grow. Outsourcing frees the resources in the parent company, which in turn allows the parent company to dedicate more time and energy to improving their core competency.

Reputed outsourcing partners hire well educated people who have the technical expertise, the knowledge and the language skills to handle data entry jobs efficiently and reliably. By allowing these experts to streamline the data entry process, businesses get two benefits at once. On the one hand, they cut costs and improve their bottom lines. On the other hand, they hire a dedicated team of professionals who specialize in data entry jobs. Thus, there is no compromise in quality. In fact, they can expect good results from reputed outsourcing partners because of the excellent remuneration they receive. The differences in foreign currencies make outsourcing a lucrative source of income for many companies.

However, it is important to remember that online data entry is fraught with risks. The first and probably the only element of risk is the quality of the service provider. Choose an outsourcing partner who has sufficient experience in the field and has a solid reputation servicing international clients. In case the outsourcing company has a branch in the same geographical location, it becomes easier to liaise with them. Experienced outsourcing companies already have enough exposure to the needs of growing companies and can be trusted to deliver excellent quality and within prescribed time limits.


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One of the Main Differences Between Statistical Analysis and Data Mining

Two methods of analyzing data that are common in both academic and commercial fields are statistical analysis and data mining. While statistical analysis has a long scientific history, data mining is a more recent method of data analysis that has arisen from Computer Science. In this article I want to give an introduction to these methods and outline what I believe is one of the main differences between the two fields of analysis.

Statistical analysis commonly involves an analyst formulating a hypothesis and then testing the validity of this hypothesis by running statistical tests on data that may have been collected for the purpose. For example, if an analyst was studying the relationship between income level and the ability to get a loan, the analyst may hypothesis that there will be a correlation between income level and the amount of credit someone may qualify for.

The analyst could then test this hypothesis with the use of a data set that contains a number of people along with their income levels and the credit available to them. A test could be run that indicates for example that there may be a high degree of confidence that there is indeed a correlation between income and available credit. The main point here is that the analyst has formulated a hypothesis and then used a statistical test along with a data set to provide evidence in support or against that hypothesis.

Data mining is another area of data analysis that has arisen more recently from computer science that has a number of differences to traditional statistical analysis. Firstly, many data mining techniques are designed to be applied to very large data sets, while statistical analysis techniques are often designed to form evidence in support or against a hypothesis from a more limited set of data.

Probably the mist significant difference here, however, is that data mining techniques are not used so much to form confidence in a hypothesis, but rather extract unknown relationships may be present in the data set. This is probably best illustrated with an example. Rather than in the above case where a statistician may form a hypothesis between income levels and an applicants ability to get a loan, in data mining, there is not typically an initial hypothesis. A data mining analyst may have a large data set on loans that have been given to people along with demographic information of these people such as their income level, their age, any existing debts they have and if they have ever defaulted on a loan before.

A data mining technique may then search through this large data set and extract a previously unknown relationship between income levels, peoples existing debt and their ability to get a loan.

While there are quite a few differences between statistical analysis and data mining, I believe this difference is at the heart of the issue. A lot of statistical analysis is about analyzing data to either form confidence for or against a stated hypothesis while data mining is often more about applying an algorithm to a data set to extract previously unforeseen relationships.



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Web Mining - Applying Data Techniques

Web mining refers to applying data techniques that discover patterns that are usually on the web. Web mining comes in three different types: content mining, structure mining and usage mining, each and every technique has its significance and roles it will depend on which company someone is.

Web usage mining

Web usage mining mainly deals with what users are mainly searching on the web. It can be either multimedia data or textual data. This process mainly deals with searching and accessing information from the web and putting the information into a one document so that it can be easily be processed.

Web structure mining

Here one uses graphs and by using graphs one can be able to analyze the structure and node of different websites how they are connected to each other. Web structure mining usually comes in two different ways:

One can be able to extract patterns from hyperlinks on different websites.

One can be able to analyze information and page structures which will describe XML and HTML usage. By doing web structure mining one can be able to know more about java script and more basic knowledge about web design.

Advantages

Web mining has many advantages which usually make technology very attractive and many government agencies and corporations use it. Predictive analysis ones does not need a lot of knowledge like in mining. Predictive analytics usually analyze historical facts and current facts about the future events. This type of mining has really helped ecommerce one can be able to do personalize marketing which later yield results in high trade volumes.

Government institutions use mining tools to fight against terrorism and to classify threat. This helps in identifying criminals who are in the country. In most companies is also applicable better services and customer relationship is usually applied it gives them what they need. By doing this companies will be able to understand the needs of customers better and later react to their needs very quickly. By doing this companies will be able to attract and retain customers and also save on production cost and utilize the insight of their customer requirements. They may even find a customer and later provide the customer with promotional offers to the customer so that they can reduce the risk of losing the customer.

Disadvantages

The worst thing that is a threat to mining is invasion of privacy. Privacy in is usually considered lost when documents of one person is obtained, disseminated or used especially when it occurs without the presence of the person who came up with the data itself. Companies collect data for various reasons and purposes. Predictive analytics is usually an area that deals mainly with statistical analysis. Predictive analytics work in different ways deal with extracting information from the data that is being used and it will predict the future trends and the behavior patterns. It is vital for one to note that that accuracy will depend on the level of the business and the data understanding of the personal user.


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