Online Web Research Services & Data Research, Data mining

Web data mining is a now become a popular activity performed by companies operating in various business areas. Some times we think why do businesses need to extract data from the Internet but data extraction from the web is needed because the web is the biggest source of information and share indexes and various other data can be found there.

Web data mining is also known as knowledge discovery from databases. Web data mining is the process of using certain algorithms, software and tools to retrieve, collect, analyze and report information from a huge pool of data. Data mining helps to extract useful information from great ample of data, which can be used for doing practical analysis for business.

Web data mining is the process to do automated mining of data from the World Wide Web. The internet has wide-range of data about everything that can be used effectively for making intelligent decisions. However, retrieving as well as filtering through such huge databases is a difficult task. Hence, there are certain web data mining tools that help to make this easier. The tools can extract related data and interpret it as per requirements.

Web data mining is gaining a lot of importance because of its vast applicability. It is being used increasingly in business applications for understanding and then predicting valuable information, like profiles of customers, industry analysis, etc. However, the use of some advanced technologies makes it a decision making tool as well. Some advanced web data mining tools can perform database addition, automated model scoring and exporting models to other applications, business templates, computing target columns, and more.

Some of the main applications of data mining are in direct marketing, e-commerce, customer relationship management, healthcare, scientific tests, telecommunications, financial services and utilities. The different kinds of data are: text mining, web mining, social networks data mining, relational databases, audio data mining and video data mining. There are several commercially available Web data mining and web usage mining software applications available.

Data is vital to the growth of business. And getting the right data at the right time is the crux of good business intelligence. Web data mining therefore has arrived on the scene at the very appropriate time, helping these enterprises to achieve a number of complex tasks that would have taken up ages but for the advent of this marvelous new technology.

Our web research provides detailed information on data mining, business intelligence data mining, web data mining, online data research, web research services. We will closely work with you; we guarantee clear, focused and relevant information that meets your specifications. If you want to know about our web research services, please visit us: http://www.outsourcingwebresearch.com.

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Data mining is also known as Knowledge Discovery in Databases (KDD). Data mining is the process of automatically searching large volumes of data for patterns. Data is derived from the word datum, being its plural term. Data comprises of a class of large number of significant statements that are measurements or observations of a variable. Data mining works on the basis of computational techniques from statistics machine learning and pattern recognition.

Data mining is the crucial process that helps companies better comprehend their customers. Data mining can be defined as ‘the nontrivial extraction of implicit, previously unknown, and potentially useful information from data’ and also as ‘the science of extracting useful information from large sets or databases’. Data mining is interpreted differently in different contexts but most often it is used in the context of a business or other organization’s need to acknowledge trends.

Just like mining for gold, data mining navigates through large databases and extracts a wealth of customer data, which is then translated into useful and predictive information. A paradigm instance of data mining is its use in a retail sales department where a store tracks the purchases of a customer who buys ample of cotton trousers. The data mining system will make an association with customer and cotton trousers and might either directly market or sale the cotton trouser to that customer or try to get the customer to buy a vast range of products. Data mining also enables automatic detection of the patterns in a database and guides marketing professionals to a better understanding of the customer psychology.

Data mining software enables users to analyze large databases to provide solutions to business decision problems. Data mining is a technology and not a business solution like statistics. The data mining software uses the information that is stored in a historical database of earlier interactions with the customers and about other aspects such as age, zip code, their feedback etc. Thus the data mining software provides an idea about the customers that would be intrigued by the new product. This enables the marketing manager to choose appropriate customers to target.

Data mining is also linked with privacy concerns particularly regarding the source of the data analyzed. For instance an employer can screen out people with diabetes or heart attack and create ethical and legal issues and elimination of costs of insurance. Besides this data mining is also used in the field of medicine to find combinations of drugs with harmful results.

Data mining should be interpreted to give beneficial results. When the data collected involves individual people, the issues concerning privacy, legality and ethics crop up.

Data mining can bring pinpoint accuracy to dales. Creating big central stores of customer data to be used all through the entire enterprise are becoming quite usual but the data warehouses are of no use if there are no proper applications for accessing and using the data in the companies.

Numerous Fortune 1000 companies all over the world have effectively installed many data mining and campaign management.

Mansi aggarwal recommends that you visit Data mining for more information.

Article Source: http://EzineArticles.com

Web data extraction is a now a popular activity performed by companies operating in almost any area. Why do businesses need to extract data from the Internet? The web is the biggest source of information – share indexes, air temperature, price updates and various other data can be found there. While there are still many companies which rely on manual data extraction, the number of firms which prefer to use specialized software has been continuously rising, especially in recent years.

One example of a successful and widely popular provider of web data extraction software is Ficstar Software, a Toronto-based company with numerous clients all over the world. Ficstar’s web data extraction technology enables organizations to quickly and easily get the results they want. The solution delivers optimized efficiency by accelerating and reducing the time needed for copying and storage. It also eliminates error-prone manual processes and ensures that extracted data is always free of man-made errors. Using the solution is also very affordable to companies which would otherwise have to spend more money on manual extraction.

One of Ficstar’s most popular products is the Web Grabber. It is able to extract data from nearly any web site, including e-commerce sites, member list directories, search engines, and others. Web Grabber dynamically locates and captures information from target sites, and automatically transforms into a text file, Excel spreadsheet, or any database format. Web Grabber products include the innovative E-commerce and Contacts solutions.

The E-commerce solution allows customers to easily search for and extracts key product details from any e-commerce web site, including product names, categories, prices, part numbers, descriptions, inventory levels, etc. It is very popular among online stores and other web-based businesses whose operation is closely connected to information contained on e-commerce sites.

The second product, Web Grabber Contacts, allows the collection of results from online business directories, member listings, and other web sites which contain contact information. This feature makes it possible for firms to quickly identify members of their target audience and collect contact information, to gather details to use in promotional campaigns, and locate professionals. It can also be used to build online business directories or residential listing sites.

These two new products are very popular as they meet some very specific needs of many modern companies. In order to meet the demand of all types of business, however, Ficstar now offers its Custom-Designed Web Grabber. The solution is customized for each customer by modifying the software to fit the specific requirements for their target web sites. The customization required for clients’ target web sites can be completed within just a few days, thus allowing customers to begin generating results almost immediately.

Customized solutions are a recent development, but are certainly part of a clearly noticeable trend of transition from manual to software-based web data extraction. Given its efficiency and affordability, software solutions will definitely conquer the field of web data extraction.

Custom Web Crawler Website Content Grabber

Article Source: Articlesbase

Data mining is the art of extracting nuggets of gold from a set of seemingly meaningless and random data. For the web, this data can be in the form of your server hit log, a database of visitors to your website or customers that have actually purchased from your web site at one time or another.Today, we will look at how examining customer purchases can give you big clues to revising/improving your product selection, offering style and packaging of products for much greater profits from both your existing customers and an increased visitor to customer ratio.

To get a feel for this, lets take a look at John, a seller of vitamins and nutritional products on the internet. He has been online for two years and has made a fairly good living at selling vitamins and such online but knows he can do better but isn't sure how.

John was smart enough to keep all customer sales data in a database which was a good idea because it is now available for analysis. The first step is for John to run several reports from his database.

In this instance, these reports include: repeat customers, repeat customer frequency, most popular items, least popular items, item groups, item popularity by season, item popularity by geographic region and repeat orders for the same products. Lets take a brief look at each report and how it could guide John to greater profits.

• Repeat Customers - If I know who my repeat customers are, I can make special offers to them via email or offer them incentive coupons (if automated) surprise discounts at the checkout stand for being such a good customer.

• Repeat Customer Frequency - By knowing how often your customer buys from you, you can start tailoring automatic ship programs for that customer where every so many weeks, you will automatically ship the products the customer needs without the hassle of reordering. It shows the customer that you really value his time and appreciate his business.

• Repeat Orders - By knowing what a customer repeatedly buys and by knowing about your other products, you can make suggestions for additional complimentaty products for the customer to add to the order. You could even throw in free samples for the customer to try. And of course, you should try to get the customer on an auto-ship program.

• Most Popular Items - By knowing what items are purchased the most, you will know what items to highlight in your web site and what items would best be used as a loss-leader in a sale or packaged with other less popular items. If a popular product costs $20 and it is bundled with another $20 product and sold for $35, people will buy the bundle for the savings provided they perceive a need of some sort for the other product.

• Least Popular Items - This fact is useful for inventory control and for bundling (described above.) It is also useful for possible special sales to liquidate unpopular merchandise.

• Item Groups - Understanding item groups is very important in a retail environment. By understanding how customer's typically buy groups of products, you can redesign your display and packaging of items for sale to take advantage of this trend. For instance, if lots of people buy both Vitamin A and Vitamin C, it might make sense to bundle the two together at a small discount to move more product or at least put a hint on their respective web pages that they go great together.

• Item Popularity by season - Some items sell better in certain seasons than others. For instance, Vitamin C may sell better in winter than summer. By knowing the seasonability of the products, you will gain insight into what should be featured on your website and when.

• Item Popularity by Geographic Region - If you can find regional buying patterns in your customer base, you have a great opportunity for personalized, targeted mailings of specific products and product groups to each geographic region. Any time you can be more specific in your offering, your close percentage increases.

As you can see, each of these elements gives very valuable information that can help shape the future of this business and how it conducts itself on the web. It will dictate what new tools are needed, how data should be presented, whether or not a personal experience is justified (i.e. one that remembers you and presents itself based on your past interactions), how and when special sales should be run, what are good loss leaders, etc.

Although it can be quite a bit of work, data mining is a truly powerful way to dramatically increase your profit without incurring the cost of capturing new customers. The cost of being more responsive to an existing customer, making that customer feel welcome and selling that customer more product more often is far less costly than the cost of constantly getting new customers in a haphazard fashion.

Even applying the basic principles shared in this article, you will see a dramatic increase in your profits this coming year. And if you don't have good records, perhaps this is the time to start a system to track all this information. After all, you really don't want to be throwing all that extra money away, do you?

Steven Chabotte is president of Big-Web Development Corp, specializing in the development of email productivity and marketing tools for the web. Steven can be reached at webmaster@maxsponder.com or you can visit our websites at http://www.maxsponder.com.

Article Source: EzineArticles.com

iNetFormFiller batch-submits your data to web forms and kills manual data entry as you send the entire selection of records to the target web forms in a single mouse click. Don’t waste your time on filling the same form over and over again!

The technology can be applied in many sectors: banking, financial, industry, IT. This particular case study shows how the solution can be implemented in banking.

In February 2008, we were contacted by a middle-sized bank located in Luxemburg. The faced the following problem.

The bank needed to validate data received from their clients. Until that time, the bank could not do without manual data entry.

PROBLEMS TO SOLVE: • Human errors related to manual data entry • Time spend on data validation • Use of scripts developed by third party

SOLUTION • Create a web-based interface for data validation • Use package software for data submission (integration of new features into existing system would be time-consuming)

BENEFITS • Only once technical effort per client • Client in charge of the data submitted • Reduction of manual data entry • Reduced intervention of third party

Says IT analyst of the bank: "It was a complicated task to find exactly what we wanted. So when we came across iNetFormFiller website, we were skeptical. We tried many products before, but they all were reliant on macro scenarios, but our web forms provide Java script and change configuration of fields as the operator enters data. iNetFormFiller proved to analyze the HTML code instead and correctly populates even the fields that are invisible with default form layout… We are not a large bank, but every day we need to process 800-900 entries, which would take 3 to 5 minutes per record manually, and 2 or 3 seconds with iNetFormFiller in automatic mode or 15-20 seconds in manual mode with step-by-step validation. In addition to saving operators’ time, iNetFormFiller is more reliable that human error-prone manual data entry. So far, we haven’t had any complaints about it."

Article Source: http://www.ArticleBiz.com

The concept of a data warehouse is to have a centralized database that

is used to capture information from different parts of the business process. The definition of a data warehouse can be determined by the collection of data and how it is used by the company and individuals that it supports. Data warehousing is the method used by businesses where they can create and maintain information for a company wide view of the data.

Data Warehouses became a distinct type of computer database during the late 1980s and early 1990s. Data warehouse evolved because demands could not be met with current operational systems. Ultimately, the need caused separate databases to be created that were designed to support decision-making information for departments or management. With this need, the development between operational and informational systems was produced.

The need has been established for a company wide view of data in operational systems. Date warehouses are designed to help management and businesses analyze data and this helps to fill the need for subject- oriented concepts. Integration is closely related to subject orientation. Data warehouses must put data from disparate sources into a consistent format. They must resolve such problems as naming conflicts and inconsistencies among units of measure. When this concept is achieved, the data warehouse is considered to be integrated.

The form of the stored data has nothing to do with whether something is a data warehouse. A data warehouse can be normalized or de-normalized. It can be a relational database, multidimensional database, flat file, hierarchical database, object database, etc. Data warehouse data often gets changed. Also, data warehouses will most often be directed to a specific action or entity.

Data warehouse success cannot be guaranteed for each project. The techniques involved can become quite complicated and erroneous data can also cause errors and failure. When management support is strong, resources committed for business values, and an enterprise vision is established, the end results may turn out to be more helpful for the organization or business. The main factors that create needs for data warehousing for most businesses today are requirements for the companywide view of quality information and departments separating informational from operational systems for improved performance for managing data.

Mickey Quinn is a father, husband, and soon to be an MIS graduate. He has a passion for team building and motivating his employees and friends. His extensive backgound in both customer service and information technology has enhanced his ability to "think outside of the box".

Article Source: EzineArticles

For decades, ABA Therapy has been the most effective form of treatment for Autism Spectrum Disorders. With many years of research having been conducted and showing time and again the effectiveness of the method, there is little doubt why it is the only treatment for Autism that most insurance companies will cover. One of the things that make ABA Training so effective is the rigorous data collection that occurs at every step along the way.

With ABA Therapy, data is collected after each section of teaching on a daily basis. This data is charted and typically graphed over a certain period of time. This helps parents, counselors, and teachers understand what areas of learning are progressing the most for a child as well as what areas need the most work. This helps significantly in designing an effective curriculum and can be the key to ensuring that a child learns everything they need to stay on par with their peers.

For home providers of ABA Therapy, data collection forms and graphs that are pre-made can be rather effective in helping parents form a curriculum that will be most effective. These graphs allow you to fill in the different things you are currently working on and help you to chart them in an easy to read and understand format that lets you see at a glance how progress is being made. By using these forms you can truly see all of the remarkable progress that your child is making from the objective viewpoint of hard data.

Many data collection packages come with a number of different types of forms. From graphs and probe sheets to reinforcement lists, there are many forms that can really help you maintain accurate data. While important for all providers of ABA Therapy, they can be especially important for parents to help them to see progress and hang-ups as data and to separate the emotional aspect of parenthood from the teaching aspect in order to best help their child.

In all, data collection is a very important part of ABA Training. Key to developing a curriculum that constantly teaches and pushes a child to learn and stay ahead, data collection helps children to learn as much as they can as quickly as possible. This can make a significant difference when preparing a child to enter school with their peers. With proper data collection, you can develop a curriculum that truly works, and when everything runs optimally, you can often help your child to not only go to school with their peers but to excel when they are there.

Garrett Butch is the father of a 6 year old with autism and is the founder of Maximum Potential. MP's courses in ABA Therapy and ABA Training were developed by 2 PhD BCBAs to empower parents and school systems and to provide effective and affordable training for school systems and parents. Visit MaximumPotentialKids.com to learn more.

Article Source: Articlesbase

Data Extraction Software is designed to automatically collect data from web pages. A lot of money can be made with Data Extraction Software, but there are two types of program - custom made and typical.Custom made solutions are designed by developers to extract from one particular source and they can't automatically adjust to another. So for example, if we are to create a custom-build data extraction program for website A, it won't work for website B, because they have different structures. Such custom made solutions cost more money than the standard ones, but they are designed for more complicated and unique situations.

Every data extraction program is based on an algorithm that has to be programmed in such a way that it will collect all the needed data from a given website. The reason why data extraction is so popular is that it saves on manual labor which can become expensive when outsourced. Data extraction software automates repetitive operations. For example, if you want to extract just the emails of every user in a given website, then you will have to pay a person to repeat the same steps over and over again like a robot. Those steps will most likely include clicking on the same place, then copying to the clipboard a piece of data that always resides on the same place on the screen.

Data extraction software is based on certain constants. By constants, I mean certain facts about a given program that do not change, no matter what. This is perhaps the only drawback of this type of software. But for the time being, it's the only way. The other way is to use artificial intelligence and make software programs think and make decisions like humans. They would have to adapt to new systems and it's almost unthinkable to consider such complicated solutions unless you are working on a very large scale.

The Bottom line here is that data extraction software is able to automate cycled operations that are otherwise expensive if handled by humans. Although the initial investment of money and time might seem expensive, it's definitely worth it in the long run, because your customized software will do the job in much less time, without the need for any human intervention.

So, if you are working on any task on the Internet, and you feel that task could be automated, then data extraction software maybe the solution you have been looking for.

For a deeper look into various data collection methods and more, such as Inventory Stock Control Software, and WMS Software then one click could provide all the answers you've been looking for.

Article Source: http://ezinearticles.com

The existing body of literature using Western blot analysis has been primarily defined with data from tumor, immortal, and primary cells growing in vitro. Collectively, results obtained over decades have been integral to the dogma that up- and down-regulation of proteins can be leveraged as Biomarkers of normal development, homeostasis, and disease. However, in contrast to tissues which are composed of multiple cell types, cell lines growing in culture which theoretically consist of clonal populations. Thus, validation or modification of western blot parameters collectively established from decades of cell line data in tissue lysates is key for Biomarker discovery.

IMGENEX can provide you with normal post mortem, cancerous, diseased, and normal adjacent clinical specimens matching your requirements. Custom collection protocols are welcomed. Specimens are available as frozen or formalin-fixed, paraffin-embedded tissue blocks, and include clinical case and detailed pathology reports, as well as final diagnosis and staging. Learn more about this service by visiting our website, or downloading our Tissue Procurement literature.


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* Tissue Arrays

* Single Tissue Slides

* Tissue & Cell Lysates

* Extraction/ Fractionation Kits

* INSTA-Blot Ready2use WB Membranes

IMGENEX India Pvt Ltd. the only biotech company in Orissa and one of its kinds in Eastern India. IMGENEX India started in Oct as an outsourcing branch of IMGENEX Corporation, San Diego, USA.Find out more information about Tissue Arrays.

Article Source: Articlesbase

Data Mining Using SAS Enterprise Miner Randall Matignon, Piedmont, CA

An Overview of SAS Enterprise Miner The following article is in regards to Enterprise Miner v.4.3 that is available in SAS v9.1.3. Enterprise Miner an awesome product that SAS first introduced in version 8. It consists of a variety of analytical tools to support data mining analysis. Data mining is an analytical tool that is used to solving critical business decisions by analyzing large amounts of data in order to discover relationships and unknown patterns in the data. The Enterprise Miner data mining SEMMA methodology is specifically designed to handling enormous data sets in preparation to subsequent data analysis. In SAS Enterprise Miner, the SEMMA acronym stands for Sampling, Exploring, Modifying, Modeling, and Assessing large amounts of data.

The reason that SAS Enterprise Miner has been given this acronym is that usually the first step in data mining is to sample the data in order to acquire a representative sample of the data. The next step is to usually explore the distribution or the range of values of each variable to the selected data set. This might be followed by modifying the data set by replacing missing values or transforming the data in order to achieve normality in the data since many of the various analytical tools depend on the variables having a normal distribution. The reason is because many of the nodes in Enterprise Miner calculate the square distances between the variables that are selected to the analysis. The next step might be to model the data. In other words, there might be interest in predicting certain variables in the data. The final steps might be to determine which models are best by assessing the accuracy between the different models that have been created.

The Ease of Use to Enterprise Miner SAS Enterprise Miner is a powerful new module introduced in version 8. But, more importantly SAS Enterprise Miner is very easy application to learn and very easy to use. SAS Enterprise Miner is visual programming with a GUI interface. The power of the SAS Enterprise Miner product is that you do not even need to know SAS programming and have very little statistical expertise in the development of your Enterprise Miner project since it is as simple as selecting icons or nodes from the EM tool palette or menu bar and dragging the icons onto the EM diagram workspace or desktop. Yet, an expert statistician can adjust and fine-tune the default settings and run the SEMMA process flow diagram to their own personal specifications. The nodes are then connected to one another in a graphical diagram workspace. SAS Enterprise Miner is visual programming with SAS icons within a graphical EM diagram workspace. It is as simple as dragging and dropping icons onto the EM diagram graphical workspace. The SAS Enterprise Miner diagram workspace environment looks similar to the desktop in Windows 95, 98, XP, and Vista. Enterprise Miner is very easy to use and can save a tremendous amount of time having to program in SAS. However, SAS Enterprise Miner has a powerful SAS Code node that brings in the capability of SAS programming into the SEMMA data mining process through the use of a SAS data step in accessing a wide range of the powerful SAS procedures into the SAS Enterprise Miner process flow diagram. Enterprise Miner produces a wide variety of statistics from descriptive, univariate, and goodness-of-fit statistics, numerous types of charts and plots, traditional regression modeling, decision tree analysis, principal component analysis, cluster analysis, association analysis, link analysis, along with automatically generated graphs that can be directed to the SAS output window.

Article Source: ArticleBiz

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?

Government, manufacturing industries, advertising firms, non-governmental organizations conduct data collection just to gather information regarding views, opinions and reactions form the public or the target consumer and use it for various decisions and actions.

Data collection just does not help the companies to launch new products or know about the public reaction to a specific issue, it is a very useful tool for statistical inferences, once the collected data is compiled. The process of data collection is the third step of the six step market research processes. Data collection can be done in two ways involving various technicalities. In this article, we shall give a brief overview of the same.

Data collection can be done in two ways - secondary data and primary data. Secondary data collection involves is the information available in books, journals, previous researches or studies and the Internet. It basically involves making use of the data already present to build or substantiate a concept.

On the other hand, primary data collection is the process of data collection through questionnaire by directly asking respondents of their opinions. Forming the right questionnaire is the most important aspect of data collection. The researcher conducting the data collection just has to be aware of the process. He should have a clear idea about the information sought by the concerned party.

Besides, the data collection officer should be able to construct the questionnaire in such a way so as to elicit the responses needed. Having constructed the questionnaire the researcher should identify the target sample. To illustrate the point clearly, we shall look into the following example.

Suppose, data collection is aimed from an area A, then, if all the residents of the data are given the questionnaire, it is called a census or in other words data collection is done from all the individuals of the specified area. One of the most common examples of data collection done by the government is census. For example the population census conducted by the US Census Bureau every ten years. On the other hand, if only twenty or thirty percent of the population living in area A are given the questionnaire, the mode of data collection would be called sampling.

The data collected from the target sample with a well-defined questionnaire will project the response of the entire population living in the area. Data collected from a sample helps to control the cost and time spent on collecting data from the population. Sample is a part of population.

Data collection just gets easier from the target sample with the help of a pretested questionnaire, which is later analyzed using statistical tests like ANOVA, Chi Square test and so on. These tests help the researcher to infer the result obtained from the data collection.

Market research/data collection is a fast growing and lucrative career option now days. One has to undertake a course in marketing, statistics and research before starting out. It is indeed very important to have a through understanding of various concepts and the theories related. Some basic terminologies related to data collection are: census, incidence, sample, population, parameters, sampling frames and so on.

There are numerous jobs available from research agencies like A.C Nielsen, fast moving consumer goods (FMCG) companies or advertising firms, some government agencies, international developmental organizations and so on.

Article Source: ArticleTrader.com

Author: Todd Wilson

Data mining isn’t screen-scraping. I know that some people in the room may disagree with that statement, but they’re actually two almost completely different concepts.
In a nutshell, you might state it this way: screen-scraping allows you to get information, where data mining allows you to analyze information. That’s a pretty big simplification, so I’ll elaborate a bit.
The term "screen-scraping" comes from the old mainframe terminal days where people worked on computers with green and black screens containing only text. Screen-scraping was used to extract characters from the screens so that they could be analyzed. Fast-forwarding to the web world of today, screen-scraping now most commonly refers to extracting information from web sites. That is, computer programs can "crawl" or "spider" through web sites, pulling out data. People often do this to build things like comparison shopping engines, archive web pages, or simply download text to a spreadsheet so that it can be filtered and analyzed.

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Author: Ambreen Tariq

ListDNA, Division of VERTX SYSTEMS, LLC today announced the release of ListDNA software utility to help you build your own marketing lists from the web.

There are few tools on the web which allows individuals and small business owners to build and generate your own unique marketing lists with e-mail, phone, fax and urls all included – easily. Sure you can buy all types of lists for $300+, and we went down this path.

We purchased an e-mail list for $1000/- and they would e-mail our product and service to 1MM opt-in e-mail users (not spam). Do you know our return on investment - $0.00 big ZERO!! Why?

The Company we bought the list from did do the work, they did send out 1MM e-mails but they did not bother to tell us that all of these e-mail users were outside USA, outside our demographics based on our target.

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Today commercial debt collection companies are useful resource to recover money from other. There are many business are use the collection agency services to recover their money form the sale of services from other business. Commercial debt recovery companies are right attitude for recover debt, since they normally follow the professional manner.

There are so many commercial debt collection companies now available although, as a business try to collect debt is decisive that you select the not only the experience but also has very high recovery rates. Mostly the high experienced debt collection company are better knowing that how to recover the maximum amount of money form others. This is the best part of any commercial debt collection company to collect the maximum amount of money that fill your business need.

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Author: Tony Jacowski


The most important factor in getting the relevant information is asking the right questions. The right questions help the respondents to understand it and answer accordingly.

Consider a situation where a help desk technician receives a call from a frantic customer saying she has spilled coffee onto a keyboard. The technician in this situation should think and dig deeper for more information about the keyboard. The technician then instructs the customer to clean it with water, as the keyboard is easily replaceable.

Within an hour, the technician receives a call from the customer's manager, demanding to know who suggested putting water on an expensive brand new laptop. The technician in this situation should have asked for more information about the keyboard, such as the brand, its specifications and so forth.

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Author: Todd Wilson

Looking at screen-scraping at a simplified level, there are two primary stages involved: data discovery and data extraction. Data discovery deals with navigating a web site to arrive at the pages containing the data you want, and data extraction deals with actually pulling that data off of those pages. Generally when people think of screen-scraping they focus on the data extraction portion of the process, but my experience has been that data discovery is often the more difficult of the two.

The data discovery step in screen-scraping might be as simple as requesting a single URL. For example, you might just need to go to the home page of a site and extract out the latest news headlines. On the other side of the spectrum, data discovery may involve logging in to a web site, traversing a series of pages in order to get needed cookies, submitting a POST request on a search form, traversing through search results pages, and finally following all of the “details” links within the search results pages to get to the data you’re actually after. In cases of the former a simple Perl script would often work just fine. For anything much more complex than that, though, a commercial screen-scraping tool can be an incredible time-saver. Especially for sites that require logging in, writing code to handle screen-scraping can be a nightmare when it comes to dealing with cookies and such.

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Author: Avadhesh Mahajan

Data Entry Outsourcing India manages your entire data entry, data digitization and manual data entry task with 99.99% accuracy. Our experienced and professional teams of data entry are dedicated to provide accurate and hassle-free data entry work at lowest possible cost in the outsourcing industry.
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Data analytics uses scientific tools to analyze data in order to draw conclusions. Almost all industry verticals are using data analytics as a tool in order to make better business decisions. Often data analytics is misunderstood as data mining but focus and purpose for both are different.
While data mining is all about sorting through huge databases in order to set up hidden relationships and identify patterns which are not revealed, data analytics focuses on obtaining conclusion.
The science of Data Analysis is generally divided into:
Exploratory data analysis: where new features in the data are discovered.
Confirmatory data analysis: where existing hypotheses are proven true or false.

In order to draw conclusions from non-numerical data like words, photographs or video, Qualitative analysis is used.

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“SCHOOL OF ANALYTICS” is a unique thought where we nurture raw and fresh talents to reach the new heights of the management ladder, where Decision making is the key to success.
Datawarehousecourses.com is a platform where we train raw and aspiring technical and management candidates to understand DATA ANALYTICS.

DATA ANALYTICS is not merely a chapter in the books or a session in a classroom, its more to that, it’s a unique combination of understanding databases, understanding data modeling, data warehousing, data marts, business intelligence tools, data mining etc.

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