Data Mining in the 21st Century: Business Intelligence Solutions Extract and Visualize

When you think of the term data mining, what comes to mind? If an image of a mine shaft and miners digging for diamonds or gold comes to mind, you're on the right track. Data mining involves digging for gems or nuggets of information buried deep within data. While the miners of yesteryear used manual labor, modern data minors use business intelligence solutions to extract and make sense of data.

As businesses have become more complex and more reliant on data, the sheer volume of data has exploded. The term "big data" is used to describe the massive amounts of data enterprises must dig through in order to find those golden nuggets. For example, imagine a large retailer with numerous sales promotions, inventory, point of sale systems, and a gift registry. Each of these systems contains useful data that could be mined to make smarter decisions. However, these systems may not be interlinked, making it more difficult to glean any meaningful insights.

Data warehouses are used to extract information from various legacy systems, transform the data into a common format, and load it into a data warehouse. This process is known as ETL (Extract, Transform, and Load). Once the information is standardized and merged, it becomes possible to work with that data.

Originally, all of this behind-the-scenes consolidation took place at predetermined intervals such as once a day, once a week, or even once a month. Intervals were often needed because the databases needed to be offline during these processes. A business running 24/7 simply couldn't afford the down time required to keep the data warehouse stocked with the freshest data. Depending on how often this process took place, the data could be old and no longer relevant. While this may have been fine in the 1980s or 1990s, it's not sufficient in today's fast-paced, interconnected world.

Real-time EFL has since been developed, allowing for continuous, non-invasive data warehousing. While most business intelligence solutions today are capable of mining, extracting, transforming, and loading data continuously without service disruptions, that's not the end of the story. In fact, data mining is just the beginning.

After mining data, what are you going to do with it? You need some form of enterprise reporting in order to make sense of the massive amounts of data coming in. In the past, enterprise reporting required extensive expertise to set up and maintain. Users were typically given a selection of pre-designed reports detailing various data points or functions. While some reports may have had some customization built in, such as user-defined date ranges, customization was limited. If a user needed a special report, it required getting someone from the IT department skilled in reporting to create or modify a report based on the user's needs. This could take weeks - and it often never happened due to the hassles and politics involved.

Fortunately, modern business intelligence solutions have taken enterprise reporting down to the user level. Intuitive controls and dashboards make creating a custom report a simple matter of drag and drop while data visualization tools make the data easy to comprehend. Best of all, these tools can be used on demand, allowing for true, real-time ad hoc enterprise reporting.


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Data Mining - Retrieving Information From Data

Data mining definition is the process of retrieving information from data. It has become very important now days because data that is processed is usually kept for future reference and mainly for security purposes in a company. Data transforms is processed into information and it is mostly used in different ways depending on what information one is extracting and from where the person is extracting the information.

It is commonly used in marketing, scientific information and research work, fraud detection and surveillance and many more and most of this work is done using a computer. This definition can come in different terms data snooping, data fishing and data dredging all this refer to data mining but it depends in which department one is. One must know data mining definition so that he can be in a position to make data.

The method of data mining has been there for so many centuries and it is used up to date. There were early methods which were used to identify data mining there are mainly two: regression analysis and bayes theorem. These methods are never used now days because a lot of people have advanced and technology has really changed the entire system.

With the coming up or with the introduction of computers and technology, it becomes very fast and easy to save information. Computers have made work easier and one can be able to expand more knowledge about data crawling and learn on how data is stored and processed through computer science.

Computer science is a course that sharpens one skill and expands more about data crawling and the definition of what data mining means. By studying computer science one can be in a position to know: clustering, support vector machines and decision trees there are some of the units that are found on computer science.

It's all about all this and this knowledge must be applied here. Government institutions, small scale business and supermarkets use data.

The main reason most companies use data mining is because data assist in the collection of information and observations that a company goes through in their daily activity. Such information is very vital in any companies profile and needs to be checked and updated for future reference just in case something happens.

Businesses which use data crawling focus mainly on return of investments, and they are able to know whether they are making a profit or a loss within a very short period. If the company or the business is making a profit they can be in a position to give customers an offer on the product in which they are selling so that the business can be a position to make more profit in an organization, this is very vital in human resource departments it helps in identifying the character traits of a person in terms of job performance.

Most people who use this method believe that is ethically neutral. The way it is being used nowadays raises a lot of questions about security and privacy of its members. Data mining needs good data preparation which can be in a position to uncover different types of information especially those that require privacy.

A very common way in this occurs is through data aggregation.

Data aggregation is when information is retrieved from different sources and is usually put together so that one can be in a position to be analyze one by one and this helps information to be very secure. So if one is collecting data it is vital for one to know the following:

    How will one use the data that he is collecting?
    Who will mine the data and use the data.
    Is the data very secure when am out can someone come and access it.
    How can one update the data when information is needed
    If the computer crashes do I have any backup somewhere.

It is important for one to be very careful with documents which deal with company's personal information so that information cannot easily be manipulated.

Victor Cases has many hobbies and interests. As well being a keen blogger and article writer for many sites, he has also recently created a site focusing on data mining definition. The site is constantly being updated and has articles such as data mining to read.


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Outsourcing Data Entry Services - Only an Experienced Player Could Enhance Your Business Value

Data is critical to every business, today. But, the same would meet the knowledge management needs of an organization only if it is processed and turned into useful information. The right information at the right time is what every business demands and maintaining a comprehensive database has become an indispensable task of every organization. However, the effective processing of data, which are usually huge, demands for the professional data entry service provider. Outsourcing the data entry functions to professional service providers would help large companies in expediting the processing of their day-to-day operations.

Advantages of partnering with an experienced service provider

A data entry BPO firm with significant expertise and experience can provide impeccable solutions to your data management requirements. A company well-equipped with security and sophisticated technology, along with experienced professionals with the capacity to handle bulk projects, can seamlessly provide the right solutions that best match with your business needs.

Domain expertise carries weight when it comes to certain tasks like finance and accounting, litigation or medical/ health-related data processing. Only a firm with deep domain expertise and skilled professionals could provide expert services. The well-experienced companies, thus, know the nuances of the business needs thereby offering superior services with 99/ 99.99% accuracy rate and best turnaround time (TAT).

Data security - Need for state-of-the-art services provider

Data privacy is one of the primary parameters considered by companies while outsourcing its non-core functions. The outsourced companies ensure data confidentiality by taking several security measures like splitting and distributing the task to more than one data entry operator, thus preventing them from having access to complete data; storing both raw and processed data in a secured or password protected files/ folders. Besides, these companies are committed to provide complete information security to their clients by entering into a legal agreement and a non-disclosure agreement with employees.

Choosing the right market for outsourcing

Even the market that you choose to outsource is very important as it could impact your business in several ways. A market that has sustained a balanced growth over a period of time despite the changes in global economic situations would be a reliable market in the long-run and this is where you can find the best BPO firms. Companies in Asia and India, in particular, have been reigning the data entry BPO industry for more than a decade now. Many small and large firms across the globe prefer outsourcing to Indian data entry firms, which have maintained and rendered superior end-results for many years now. Zeroing in on the right market and the right company helps vendors enjoy quick services at cost-effective rates. In addition, the cut-throat competition prevailing in the industry allows big companies to select the best outsourcing company that meets their specifications. This way a large amount of overhead costs is eliminated, besides enabling the companies to focus on their core business activities.

Apart from providing quality offshore data entry solutions, companies that have been in the industry for years are vying to deliver value to its vendors by quick processing, reducing the data security risk and providing competitive rates thereby enhancing business performance.


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Data Entry Services Help Your Business Flow Smoothly

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

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

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


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Why Outsource Data Entry Service?

Data entry is one of the most neglected responsibilities for any organization. Many organizations can not provide much attention to the data entry departments compare to other departments of the firm. So it is beneficial for them to outsource data entry services to bpo companies. Outsourcing is one of the most cost effective and reliable way to manage your business data entry.

If you think to outsource bpo services, then India is the most preferred country to outsource data entry, data processing, data conversion and many more bpo services at affordable rate. To save money and time, India is the central place in the world to outsource data entry services.

Some of other reimbursements of outsourcing like:

- Reduced operating cost
- No need to hire and train employee
- Make able you to focus on your core business
- Take advantages of bpo professionals
- Saved money and time can be invested in the other areas of business

Outsourcing is the profitable option available for any businesses because it has maximum benefits which boosts up your business performance, increases productivity, smoothly and effectively running your database management system and work flow.

Outsourcing services make available addition benefits such as integrating high quality processes, the advanced technology, well established infrastructure and expert professionals are capable to achieve better and cover the entire range of data entry services at lowest rates with 99.98% accuracy.

So, outsource your requirements to a reliable bpo company who is accomplished to complete data entry needs with successfully and provide ideal customized solutions for your entire organization requirements.

BPO industry engaged in providing absolute services give quick, well-organized and secure solutions to retain their place in competitive outsourcing market. Many organizations provide high level of accuracy with complete confidentiality. These companies also utilize the services of proofreaders in an effort to give high accurate service.


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Importance of Data Mining Services in Business

Data mining is used in re-establishment of hidden information of the data of the algorithms. It helps to extract the useful information starting from the data, which can be useful to make practical interpretations for the decision making.
It can be technically defined as automated extraction of hidden information of great databases for the predictive analysis. In other words, it is the retrieval of useful information from large masses of data, which is also presented in an analyzed form for specific decision-making. Although data mining is a relatively new term, the technology is not. It is thus also known as Knowledge discovery in databases since it grip searching for implied information in large databases.
It is primarily used today by companies with a strong customer focus - retail, financial, communication and marketing organizations. It is having lot of importance because of its huge applicability. It is being used increasingly in business applications for understanding and then predicting valuable data, like consumer buying actions and buying tendency, profiles of customers, industry analysis, etc. It is used in several applications like market research, consumer behavior, direct marketing, bioinformatics, genetics, text analysis, e-commerce, customer relationship management and financial services.

However, the use of some advanced technologies makes it a decision making tool as well. It is used in market research, industry research and for competitor analysis. It has applications in major industries like direct marketing, e-commerce, customer relationship management, scientific tests, genetics, financial services and utilities.

Data mining consists of major elements:

    Extract and load operation data onto the data store system.
    Store and manage the data in a multidimensional database system.
    Provide data access to business analysts and information technology professionals.
    Analyze the data by application software.
    Present the data in a useful format, such as a graph or table.

The use of data mining in business makes the data more related in application. There are several kinds of data mining: text mining, web mining, relational databases, graphic data mining, audio mining and video mining, which are all used in business intelligence applications. Data mining software is used to analyze consumer data and trends in banking as well as many other industries.


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Information About Data Mining

The potential offered by data mining can be included in the category of the processes of the commercial enterprises and looking for information is not a purpose itself, but it is a very useful process if it is transformed into a real action. Thus, enterprises can choose to react to the different situations created by reality, such as the reduction of the number of customers, the loss of certain markets and so on. The next step after making this choice is the proper exploitation of the data, using different algorithms.

Very often, data mining turns out to be a complete failure and not a success, the measures adopted bot always being appropriate for the information obtained. All these elements which are mentioned above lead to the idea that there is a cycle with data mining and that there are four stages when it comes to this process.

First of all, you have to define the commercial possibilities and the data. Then, you have to get information from the existent data collections using data mining techniques, after which you have to make decisions referring to the subsequent actions using the results you obtain. Last but not least, you have to measure your results properly in order to identify other ways of exploiting the data, too. Of course, you should only be looking at the concrete results because the rest of them can meddle with the outcomes and can alter the quality of the ones you should be getting. Therefore, if you take these steps into consideration, you should be properly using data mining in administrating the activity of your company.


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Various Data Mining Techniques

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

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

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

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

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

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

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


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Data Management Services

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

Entering of data

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

EDC

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

Data changing

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

Managing data service

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

Data extraction and cleansing

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

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


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Data Extraction Services - A Helpful Hand For Large Organization

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

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

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

The different types of Data Extraction Services:

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

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

Advantages of Outsourcing Data Extraction Services:

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

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


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What is Data Mining? Why Data Mining is Important?

Searching, Collecting, Filtering and Analyzing of data define as data mining. The large amount of information can be retrieved from wide range of form such as different data relationships, patterns or any significant statistical co-relations. Today the advent of computers, large databases and the internet is make easier way to collect millions, billions and even trillions of pieces of data that can be systematically analyzed to help look for relationships and to seek solutions to difficult problems.

The government, private company, large organization and all businesses are looking for large volume of information collection for research and business development. These all collected data can be stored by them to future use. Such kind of information is most important whenever it is require. It will take very much time for searching and find require information from the internet or any other resources.

Here is an overview of data mining services inclusion:

* Market research, product research, survey and analysis
* Collection information about investors, funds and investments
* Forums, blogs and other resources for customer views/opinions
* Scanning large volumes of data
* Information extraction
* Pre-processing of data from the data warehouse
* Meta data extraction
* Web data online mining services
* data online mining research
* Online newspaper and news sources information research
* Excel sheet presentation of data collected from online sources
* Competitor analysis
* data mining books
* Information interpretation
* Updating collected data

After applying the process of data mining, you can easily information extract from filtered information and processing the refining the information. This data process is mainly divided into 3 sections; pre-processing, mining and validation. In short, data online mining is a process of converting data into authentic information.

The most important is that it takes much time to find important information from the data. If you want to grow your business rapidly, you must take quick and accurate decisions to grab timely available opportunities.

Outsourcing Web Research is one of the best data mining outsourcing organizations having more than 17 years of experience in the market research industry. To know more information about our company please contact us.


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Strengthen Your Website Content With Online Database Access

Website content, as articles, has taken center stage as web publishers scramble to differentiate their online offers. As both the quantity and quality of articles have accelerated, so too have online directories. These directories often resemble mere lists, but they can be powerful content additions that serve to deepen the value of the overall selling proposition by helping users in locating critical, related resources that for the visitor is otherwise much too time consuming.

On today's websites, it is not uncommon to find online databases designed to provide the data-hungry website visitor with more comprehensive database management functions which are far superior to list-style directories. At a minimum, we find web-driven data pages that include search and display functions which facilitate quick and easy manipulation of back-end SQL databases. Many sites also include options to add, edit, delete, print, and even download data directly from the database to the desktop, all enabled with multiple levels of login/password security. While this is not revolutionary, the technical expertise required to build database-driven web pages has been the domain of more sophisticated online publishers who not only owned the back end database outright, but possessed the required expertise to build and maintain such access for their loyal constituents.

But that has all changed. A flurry of new, low-cost desktop tools have entered the scene, leveling the playing field for the budget-strapped internet marketer who, until recently, was limited to throwing in a basic "telephone book" style directory in an attempt to bolster his value proposition.

Three such tool categories warrant a closer look:

Web data extraction tools costing less than $400 enable web content, as "repeating data", to be easily extracted to MS Excel, MS Access, or virtually any SQL database in high volume. This data serves to build, or at least augment the publisher's's new online database. (Ideally, one should first obtain permission from the website owner before scraping large volumes of data).

The next challenge is to manipulate the collected data now resident in multiple files, and often in disparate data formats. Though list processing applications have long been available, lower cost tools now offer powerful merge/purge capabilities without the need to import and export files in the process. Some simple routines and the data is ready to upload to the database on the host web server.

Finally, the publisher builds the web pages which access the database. Perhaps most exciting is the arrival of a wide variety of desktop code generators, many which are open source, that allow a non-programmer to build customized web pages that rival the database search, display, add, edit,delete and download capabilities previously reserved for the more technical publisher. No longer is the web publisher required to know a single SQL command to accomplish this feat. Amazingly, most of these tools generate pure PHP or PERL code. All that remains is to upload the generated code to the host database and the project is complete. The website now houses a "living, breathing" database, to the extent that the publisher desires to maintain fresh data.

One of the more common, and simple applications of database-driven web pages is to build versatile Frequently Asked Questions (FAQ) pages. Questions and answers can be queried by category (e.g. pricing, product) or keyword (e.g. sporting goods), while enriching the users support experience.

How can such newfound capabilities be monetized? The possibilities are plenty. Limited datasets can be made freely searchable and viewable for casual visitors, though it's usually wise to request that the user register even if membership is free. The idea is to prime the pump, getting casual users to thirst for more comprehensive database access. Extended and full database access can be reserved only for paid members.

Never has a publisher had such power to build data-rich content that can serve to immediately strengthen his unique selling sales proposition. In the old paradigm, he who owned the data held all the power. Today, data is everywhere for the internet entrepreneur. By applying the latest database tools, any website publisher can now cement the most loyal of customer relationships by ensuring that his customer has a reason to keep coming back.

Web visitors have a difficult enough time sorting out the perceived sameness of online offerings. For the content builder, there are few better methods to establish and lock in immediate credibility with customers than to implement an easily accessible database that underscores the site's overall content theme.


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Outsourcing Data Entry Work

As the business world develops quickly, more and more companies are unable to manage large quantities of data coming fast and furious day in day out. They need to spend time and effort on other important issues related to their businesses instead of wasting all just on data entry.

So what they did next is to outsource those work to specialized companies and freelance individuals who will be keen to take over.

By outsourcing, they would be relieved greatly from the pressure of handling all those workload and focus on immediate tasks like marketing strategies, promotion, customer follow-up and support.

Moreover, outsourcing is cheaper and less time consuming from conventional recruitment which they ended up spending more money and time teaching the newcomers and making sure they understand quickly.

It is also the best option for all business needs requiring advanced pool of talent. Such as experienced and skilled professionals who would have no problem handling all related tasks entrusted by companies.

Now that full training is provided by companies, the client companies can be relieved from of training the employees again and again just to make sure they understand completely before entrusting the work to them.

Outsourcing data entry work also helps them to track down and update all incoming latest data 24 hours a day and 365 days a year on autopilot. Because of this, there is no limit as to how much work the client companies can outsource so long as they have the affordability and trust whoever they outsource to do a great job.

The most common work outsourced so far are bills, legal documents, invoices, manuals, medical billing, payroll, research reports, surveys, tax forms etc.

Most data processing companies have safety measures such as double keying process which involves rekeying data into different file formats. After which, the files are compared electronically with each other to provide accurate results to clients.

Henceforth selecting a legitimate company for outsourcing would help the companies get relief from most of the data processing problems.

Some companies are quite versatile in data processing and are more than willing to help clients in handling their projects irregardless of race and language.

Speaking of which, it is one of the main reasons for outsourcing being popular among clients to those companies. It also enables them to get the necessary output in their desired online format like CD-R, CD-RW, FTP just to name a few.

Apart from versatility, they have up-to-date technologies based on the current trends in relevant industry. These will get all the outsourced work accomplished quickly, flawlessly and easily.

As of today, outsourcing to developing countries is pretty common. This helps clients achieve their desired output for comparative lesser amount.

Just because those countries are developing does not mean the people are low standard in qualities. They are highly committed and well-trained to perform just as well as those in developed countries. The only difference is they are willing to accept lower rates and still deliver high quality work.

Overall, choosing a reliable company to outsource your work is a perfect solution to cut costs, get things done faster and free up your time on other things.


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What's Your Excuse For Not Using Data Mining?

In an earlier article I briefly described how data mining and RFM analysis can help marketers be more efficient (read... increased marketing ROI!). These marketing analytics tools can significantly help with all direct marketing efforts (multichannel campaign management efforts using direct mail, email and call center) and some interactive marketing efforts as well. So, why aren't all companies using it today? Well, typically it comes down to a lack of data and/or statistical expertise. Even if you don't have data mining expertise, YOU can benefit from data mining by using a consultant. With that in mind, let's tackle the first problem -- collecting and developing the data that is useful for data mining.

The most important data to collect for data mining include:

oTransaction data - For every sale, you at least need to know the product and the amount and date of the purchase.

oPast campaign response data - For every campaign you've run, you need to identify who responded and who didn't. You may need to use direct and indirect response attribution.

oGeo-demographic data - This is optional, but you may want to append your customer file/database with consumer overlay data from companies like Acxiom.

oLifestyle data - This is also an optional append of indicators of socio-economic lifestyle that are developed by companies like Claritas. All of the above data may or may not exist in the same data source. Some companies have a single holistic view of the customer in a database and some don't. If you don't, you'll have to make sure all data sources that contain customer data have the same customer ID/key. That way, all of the needed data can be brought together for data mining.

How much data do you need for data mining? You'll hear many different answers, but I like to have at least 15,000 customer records to have confidence in my results.

Once you have the data, you need to massage it to get it ready to be "baked" by your data mining application. Some data mining applications will automatically do this for you. It's like a bread machine where you put in all the ingredients -- they automatically get mixed, the bread rises, bakes, and is ready for consumption! Some notable companies that do this include KXEN, SAS, and SPSS. Even if you take the automated approach, it's helpful to understand what kinds of things are done to the data prior to model building.

Preparation includes:

oMissing data analysis. What fields have missing values? Should you fill in the missing values? If so, what values do you use? Should the field be used at all?

oOutlier detection. Is "33 children in a household" extreme? Probably - and consequently this value should be adjusted to perhaps the average or maximum number of children in your customer's households.

oTransformations and standardizations. When various fields have vastly different ranges (e.g., number of children per household and income), it's often helpful to standardize or normalize your data to get better results. It's also useful to transform data to get better predictive relationships. For instance, it's common to transform monetary variables by using their natural logs.

oBinning Data. Binning continuous variables is an approach that can help with noisy data. It is also required by some data mining algorithms.

More to come on data mining for marketers in my next article.


Source: http://ezinearticles.com/?Whats-Your-Excuse-For-Not-Using-Data-Mining?&id=3576029

Top Data Mining Tools

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

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

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

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

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


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

Outsourcing Data Entry Services

Data entry services are among the many benefits that the IT sector is providing to corporate firms worldwide. These services often range from simple text data entry to alpha numerical entries requiring calculations such as bill processing for clients. To meet the demands for high quality and accurate textual and numerical data entry jobs, most outsourcing firms are employing the services of talented operators who are skilled in fast keyboard operations and word processing software.

Often business firms find it difficult to manage their huge data manipulation jobs and are compelled to outsource such jobs. In order to meet the deadlines in document entry jobs, the Business Processing Outsourcing (BPOs) units that are engaged in providing data entry services are offering their services in a fast, competitive and efficient manner. Quality in work is given top priority by these BPOs and to ensure this, they utilize the services of proofreaders who always double check the processed data for errors.

Data entry service providers also provide customized document entry services, suiting the requirements of client companies. Common data entry jobs being offered by BPOs include:

o Online data entry
o Offline data entry
o Data capture and conversion
o Document processing and management
o Medical document entry
o Insurance claim processing
o Census document entry

To cater to the increasing need of business firms to process their critical data as early as possible, most document processing firms have their own backup centers with sufficient employees. Most BPO firms operate round the clock to ensure that no work remains in pending state. The 24 hr operations of these firms also ensure that the daily requirements in critical data processing such as insurance claim processing are done in a timely manner.

Most BPOs, with the help of advanced IT equipments and professional trainers, can instantly train employees for mission critical data entry services and thus are capable of providing quality services for both short term as well as long term requirements of clients. The high quality training ensures that all their employees carry out the assigned jobs efficiently and accurately within the proposed time frame.

With the outsourcing of data entry services, most companies are able to concentrate on improving their core services and need only worry less about their daily clerical works. To add value to the services, excellent customer support is also provided by these document processing service providers. The quality document processing services provided by these firms help many corporate firms to stay competitive and profitable in the challenging business arena of today.

Managed Outsource Solutions (MOS) is a US company providing managed outsource solutions that are focused on several industries, including medical, legal, information technology and media. Outsourcing data entry we can help you process your paper work, increase your turn around time and make sure that all files or data is updated as required.


Source: http://ezinearticles.com/?Outsourcing-Data-Entry-Services&id=1523730

Three Common Methods For Web Data Extraction

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

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

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

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

Raw regular expressions and code

Advantages:

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

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

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

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

Disadvantages:

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

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

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

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

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

Ontologies and artificial intelligence

Advantages:

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

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

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

Disadvantages:

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

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

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

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

Screen-scraping software

Advantages:

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

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

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

Disadvantages:

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

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

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

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

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


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