The Case For Offshore Data Entry

Almost everything is run by computers today. They have become an integral part of our lives, handling everything from business to travel to entertainment and even most of our personal matters. Sometimes it's hard to remember that it all started with just a handful of large and expensive mainframes, and the business of using those mainframes was called data processing. Collecting data and feeding it into those giant machines was a time-consuming procedure as the data was punched onto cards before it could be processed and analyzed.

Things have changed dramatically in computing over the past 50 years. Processing power is essentially free today, with the chips in notebook computers and even our smartphones infinitely quicker than those mainframes at the dawn of the information age. What hasn't changed nearly as much is data entry. That largely remains an error-prone process that often requires manual labor and/or intervention. Think about all the ways we enter data and you quickly see that it's the most critical point in the process, the point that consumes the most time and also the point where errors occur most likely.

A lot of the innovation in computerized systems today is not in building better and faster computers, but in perfecting data capture and data entry systems. There are scanners that read barcodes, systems that have radio frequency tags, machines that scan and convert forms, and numerous other ways to make the process of converting data into machine-readable form. All of this has made data entry faster, cheaper and more reliable, but it still remains perhaps the most critical bottleneck. Why?

Because a lot of data is generated by people, and people think and act differently from machines. When people fill out forms by hand, they may make errors, cross things out, and their handwriting may be nearly illegible. Even when they use an electronic form, they may use the wrong fields, or enter the data in a way that the computer cannot read. There are all sorts of efforts to automatically "clean" data, but even today, a lot of data must still be either entered by hand, or at least scanned and fixed by hand. And that can be enormously time consuming and therefore expensive.

There are other aspects of data entry that can burn up a lot of time. Data conversion is one of them. There are so many different data formats today that data conversion is a major issue. Even converting from one version of a format to another can totally throw the process and require extensive manual intervention. Something as seemingly simple as converting from one version of Microsoft Word to another can be hugely time-consuming, let alone conversions to and from formats such as XML, SGML, XLS or CSV. Add to that image conversion, data indexing, or data mining, and things can quickly go from time consuming to overwhelming.

This is where it pays to farm things out to an experienced professional data entry service. It's also one of the areas where outsourcing makes most sense. Getting the raw data or data files to a reliable, inexpensive offshore data entry service for entry and cleaning, or even converting and processing in a number of ways, greatly reduces local costs. It also allows local staff to spend their time mot productively, by analyzing and using data to manage business and maximize productivity. It's a win-win situation for all involved.




Source: http://ezinearticles.com/?The-Case-For-Offshore-Data-Entry&id=1969799

Data Mining

Data mining is the retrieving of hidden information from data using algorithms. Data mining helps to extract useful information from great masses of data, which can be used for making practical interpretations for business decision-making. It is basically a technical and mathematical process that involves the use of software and specially designed programs. Data mining is thus also known as Knowledge Discovery in Databases (KDD) since it involves searching for implicit information in large databases. The main kinds of data mining software are: clustering and segmentation software, statistical analysis software, text analysis, mining and information retrieval software and visualization software.

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 customer buying behavior and buying trends, profiles of customers, industry analysis, etc. It is basically an extension of some statistical methods like regression. However, the use of some advanced technologies makes it a decision making tool as well. Some advanced data mining tools can perform database integration, automated model scoring, exporting models to other applications, business templates, incorporating financial information, computing target columns, and more.

Some of the main applications of data mining are in direct marketing, e-commerce, customer relationship management, healthcare, the oil and gas industry, scientific tests, genetics, telecommunications, financial services and utilities. The different kinds of data are: text mining, web mining, social networks data mining, relational databases, pictorial data mining, audio data mining and video data mining.

Some of the most popular data mining tools are: decision trees, information gain, probability, probability density functions, Gaussians, maximum likelihood estimation, Gaussian Baves classification, cross-validation, neural networks, instance-based learning /case-based/ memory-based/non-parametric, regression algorithms, Bayesian networks, Gaussian mixture models, K-Means and hierarchical clustering, Markov models, support vector machines, game tree search and alpha-beta search algorithms, game theory, artificial intelligence, A-star heuristic search, HillClimbing, simulated annealing and genetic algorithms.

Some popular data mining software includes: Connexor Machines, Copernic Summarizer, Corpora, DocMINER, DolphinSearch, dtSearch, DS Dataset, Enkata, Entrieva, Files Search Assistant, FreeText Software Technologies, Intellexer, Insightful InFact, Inxight, ISYS:desktop, Klarity (part of Intology tools), Leximancer, Lextek Onix Toolkit, Lextek Profiling Engine, Megaputer Text Analyst, Monarch, Recommind MindServer, SAS Text Miner, SPSS LexiQuest, SPSS Text Mining for Clementine, Temis-Group, TeSSI®, Textalyser, TextPipe Pro, TextQuest, Readware, Quenza, VantagePoint, VisualText(TM), by TextAI, Wordstat. There is also free software and shareware such as INTEXT, S-EM (Spy-EM), and Vivisimo/Clusty.



Source: http://ezinearticles.com/?Data-Mining&id=196652

Is Web Scraping Relevant in Today's Business World?

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

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

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

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

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

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



Source: http://ezinearticles.com/?Is-Web-Scraping-Relevant-in-Todays-Business-World?&id=7091414

Data Mining for Dollars

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

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

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

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

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

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

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

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

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



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

Data Mining Questions? Some Back-Of-The-Envelope Answers

Data mining, the discovery and modeling of hidden patterns in large volumes of data, is becoming a mainstream technology. And yet, for many, the prospect of initiating a data mining (DM) project remains daunting. Chief among the concerns of those considering DM is, "How do I know if data mining is right for my organization?"

A meaningful response to this concern hinges on three underlying questions:

    Economics - Do you have a pressing business/economic need, a "pain" that needs to be addressed immediately?
    Data - Do you have, or can you acquire, sufficient data that are relevant to the business need?
    Performance - Do you need a DM solution to produce a moderate gain in business performance compared to current practice?

By the time you finish reading this article, you will be able to answer these questions for yourself on the back of an envelope. If all answers are yes, data mining is a good fit for your business need. Any no answers indicate areas to focus on before proceeding with DM.

In the following sections, we'll consider each of the above questions in the context of a sales and marketing case study. Since DM applies to a wide spectrum of industries, we will also generalize each of the solution principles.

To begin, suppose that Donna is the VP of Marketing for a trade organization. She is responsible for several trade shows and a large annual meeting. Attendance was good for many years, and she and her staff focused their efforts on creating an excellent meeting experience (program plus venue). Recently, however, there has been declining response to promotions, and a simultaneous decline in attendance. Is data mining right for Donna and her organization?

Economics - Begin with economics - Is there a pressing business need? Donna knows that meeting attendance was down 15% this year. If that trend continues for two more years, turnout will be only about 60% of its previous level (85% x 85% x 85%), and she knows that the annual meeting is not sustainable at that level. It is critical, then, to improve the attendance, but to do so profitably. Yes, Donna has an economic need.

Generally speaking, data mining can address a wide variety of business "pains". If your company is experiencing rapid growth, DM can identify promising new retail locations or find more prospects for your online service. Conversely, if your organization is facing declining sales, DM can improve retention or identify your best existing customers for cross-selling and upselling. It is not advisable, however, to start a data mining effort without explicitly identifying a critical business need. Vast sums have been spent wastefully on mining data for "nuggets" of knowledge that have little or no value to the enterprise.

Data - Next, consider your data assets - Are sufficient, relevant data available? Donna has a spreadsheet that captures several years of meeting registrations (who attended). She also maintains a promotion history (who was sent a meeting invitation) in a simple database. So, information is available about the stimulus (sending invitations) and the response (did/did not attend). This data is clearly relevant to understanding and improving future attendance.

Donna's multi-year registration spreadsheet contains about 10,000 names. The promotion history database is even larger because many invitations are sent for each meeting, both to prior attendees and to prospects who have never attended. Sounds like plenty of data, but to be sure, it is useful to think about the factors that might be predictive of future attendance. Donna consults her intuitive knowledge of the meeting participants and lists four key factors:

    attended previously
    age
    size of company
    industry

To get a reasonable estimate for the amount of data required, we can use the following rule of thumb, developed from many years of experience:

Number of records needed ≥ 60 x 2^N (where N is the number of factors)

Since Donna listed 4 key factors, the above formula estimates that she needs 960 records (60 x 2^4 = 60 x 16). Since she has more than 10,000, we conclude Yes, Donna has relevant and sufficient data for DM.

More generally, in considering your own situation, it is important to have data that represents:

    stimulus and response (what was done and what happened)
    positive and negative outcomes

Simply put, you need data on both what works and what doesn't.

Performance - Finally, performance - Is a moderate improvement required relative to current benchmarks? Donna would like to increase attendance back to its previous level without increasing her promotion costs. She determines that the response rate to promotions needs to increase from 2% to 2.5% to meet her goals. In data mining terms, a moderate improvement is generally in the range of 10% to 100%. Donna's need is in this interval, at 25%. For her, Yes, a moderate performance increase is needed.

The performance question is typically the hardest one to address prior to starting a project. Performance is an outcome of the data mining effort, not a precursor to it. There are no guarantees, but we can use past experience as a guide. As noted for Donna above, incremental-to-moderate improvements are reasonable to expect with data mining. But don't expect DM to produce a miracle.

Conclusion

Summarizing, to determine if data mining fits your organization, you must consider:

    your business need
    your available data assets
    the performance improvement required

In the case study, Donna answered yes to each of the questions posed. She is well-positioned to proceed with a data mining project. You, too, can apply the same thought process before you spend a single dollar on DM. If you decide there is a fit, this preparation will serve you well in talking with your staff, vendors, and consultants who can help you move a data mining project forward.



Source: http://ezinearticles.com/?Data-Mining-Questions?-Some-Back-Of-The-Envelope-Answers&id=6047713

What You Should Know About Data Mining

Often called data or knowledge discovery, data mining is the process of analyzing data from various perspectives and summarizing it into useful information to help beef up revenue or cut costs. Data mining software is among the many analytical tools used to analyze data. It allows categorizing of data and shows a summary of the relationships identified. From a technical perspective, it is finding patterns or correlations among fields in large relational databases. Find out how data mining works and its innovations, what technological infrastructures are needed, and what tools like phone number validation can do.

Data mining may be a relatively new term, but it uses old technology. For instance, companies have made use of computers to sift through supermarket scanner data - volumes of them - and analyze years' worth of market research. These kinds of analyses help define the frequency of customer shopping, how many items are usually bought, and other information that will help the establishment increase revenue. These days, however, what makes this easy and more cost-effective are disk storage, statistical software, and computer processing power.

Data mining is mainly used by companies who want to maintain a strong customer focus, whether they're engaged in retail, finance, marketing, or communications. It enables companies to determine the different relationships among varying factors, including staffing, pricing, product positioning, market competition, and social demographics.

Data mining software, for example, vary in types: statistical, machine learning, and neural networks. It seeks any of the four types of relationships: classes (stored data is used for locating data in predetermined groups), clusters (data are grouped according to logical relationships or consumer preferences), associations (data is mined to identify associations), and sequential patterns (data is mined to estimate behavioral trends and patterns). There are different levels of analysis, including artificial neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction, and data visualization.

In today's world, data mining applications are available on all size systems from client/server, mainframe, and PC platforms. When it comes to enterprise-wide applications, the size usually ranges from 10 gigabytes to more than 11 terabytes. The two important technological drivers are the size of the database and query complexity. A more powerful system is required with more data being processed and maintained, and with more complex and greater queries.

Programmable XML web services like phone number validation will assist your company in improving the quality of your data needed for data mining. Used to validate phone numbers, a phone number validation service allows you to improve the quality of your contact database by eliminating invalid telephone numbers at the point of entry. Upon verification, phone number and other customer information can work wonders for your business and its constant improvement.



Source: http://ezinearticles.com/?What-You-Should-Know-About-Data-Mining&id=6916646

How Data Mining Can Help in Customer Relationship Management Or CRM?

Customer relationship management (CRM) is critical activity of improvising customer interactions while at the same time making the interactions more amicable through individualization. Data mining utilizes various data analysis and modeling methods to detect specific patterns and relationships in data. This helps in understanding what a customer wants and forecasting what they will do.

Using Data mining you can find out right prospects and offer them right products. This results in improved revenue because you can respond to each customer in best way using fewer resources.

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

Let me explain above steps in detail.

Define the business objective:
Every CRM process has one or more business objective for which you need to construct the suitable model. This model varies depending on your specific goal. The more precise your statement for defining the problem is the more successful is your CRM project.

Construct a marketing database:
This step involves creation of constructive marketing database since your operational data often don't contain the information in the form you want it. The first step in building your database is to clean it up so that you can construct clean models with accurate data.

The data you need may be scattered across different databases such as the client database, operational database and sales databases. This means you have to integrate the data into a single marketing database. Inaccurately reconciled data is a major source of quality issues.

Analyze the data:
Prior to building a correct predictive model, you must analyze your data. Collect a variety of numerical summaries (such as averages, standard deviations and so forth). You may want to generate a cross-section of multi-dimensional data such as pivot tables.

Graphing and visualization tools are a vital aid in data analysis. Data visualization most often provides better insight that leads to innovative ideas and success.



Source: http://ezinearticles.com/?How-Data-Mining-Can-Help-in-Customer-Relationship-Management-Or-CRM?&id=4572272

Database Mining

The term database mining refers to the process of extracting information from a set database and transforming that into understandable information. The data mining process is also known as data dredging or data snooping. The consumer focused companies into retail, financial, communication, and marketing fields are using data mining for cost reduction and increase revenues. This process is the powerful technology, which helps the organisations to focus on the most important and relevant information from their collected data. Organisations can easily understand the potential customers and their behaviour with this process. By predicting behaviours of future trends the recruitment process outsourcing firms assists the multiple organisations to make proactive and profitable decisions in their business. The database mining term is originated from the similarities between searching for valuable information in large databases and mining a mountain for a vein of valuable crystal.

Recruitment process outsourcing firm helps the organisation for the betterment of their future by analyzing the data from distinctive dimensions or angles. From the business point of view, the data mining and data entry services leads the organisation to increase their profitability and customer demands. Data mining process is must for every organisation to survive in the competitive market and quality assurance. Now a day the data mining services are actively utilised and adapted by many organisations to achieve great success and analyse competitor growth, profit analysis, budget, and sales etc. The data mining is a form of artificial intelligence that uses the automated process to find required information. You can easily and swiftly plan your business strategy for the future by finding and collecting the equivalent information from huge data.

With the advanced analytics and modern techniques, the database mining process uncovers the in-depth business intelligence. You can ask for the certain information and let this process provide you information, which can lead to an immense improvement in your business and quality. Every organisation holds a huge amount of data in their database. Due to rapid computerisation of business, the large amount of data gets produced by every organisation and then database mining comes in the picture. When there are problems arising and challenges addressing in the database management of your organisation, the fundamental usage of data mining will help you out with maximum returns. Thus, from the strategic point of view, the rapidly growing world of digital data will depend on the ability of mining and managing the data.



Source: http://ezinearticles.com/?Database-Mining&id=7292341

Beneficial Data Collection Services

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

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

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

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



Source: http://ezinearticles.com/?Beneficial-Data-Collection-Services&id=5879822

Every Business Organization Needs Data Entry Services

Data entry is the main component of any business firm. They use this to maintain records of all sorts in a properly way. Although it seems to be an easier task but this is not the scenario, the work has to be done very cautiously and efficiently by the professional as data is very crucial. Data is priceless for any organization irrespective of their size and strength. Today, huge changes in the business industry have taken place and so businesses are adopting such new advanced techniques. These high end technologies have helped the data entry services in becoming much easier and efficient than ever before. If you are seeking to this service then must be prepared to spend more for this. So hiring this service will certainly help your business towards upward growth. Well, being the owner of your business, you are the best person to judge what will be a good strategy for your business. You can either hire a professional or can hire an outside firm to assist your data entry services task.

The newer methods of data entry services have over lapped the older and traditional methods of this service. Earlier, this service was done manually and obviously in-accuracy was found much more. So, information technology enabled services have come up with the new process that has made this service highly accurate and much easier. Indeed, every business wants to deal with this service very efficiently and accurately and so many have taken this highly enabled service for their firm. Data entry services are the key aspect of any business organization and every business needs a proper system to maintain its data and records. As data is crucial aspect of any firm irrespective of specialization or size and so they are in need of such an efficient system that can undertake their task.

An in-house data entry services would be more advantageous as you can keep a watch on the task done by professional. You can look into the procedure and other stuff that they do for your business. This can be bit expensive for your business as you will have to pay more as being an employee they are eligible for bonuses, allowances and other stuffs. If you are not satisfied with this option then you can undertake the services of a third party vendor. You can hand-over your entire task of data entry to them and can relieve of getting an efficient services. This can truly relieve you of getting a better service from them as you can get your task done in the way you desire. This option has proved to be more advantageous and proficient for many businesses. Now a day's data conversion process is highly accessed by many business firms and so gaining momentum on a large scale.

Data conversion is being done without any hassle and brings more customers to buy the products. Outsourcing of data entry services has seen huge success and businesses have seen huge profits through this service. This service has proved as a cost effective business strategy for businesses and have seen huge surge in their revenue.So, it's quite obvious that hiring data entry services from a third party vendor is better for the business then why to hire an in-house professional.



Source: http://ezinearticles.com/?Every-Business-Organization-Needs-Data-Entry-Services&id=596342

The A B C D of Data Mining Services

If you are very new to the term 'data mining', let the meaning be explained to you. It is form of back office support services that are being offered by many call centers to analyze data from numerous resources and amalgamate them for some useful task. The business establishments in the present generation need to develop a strategy that helps them to cooperate with the market trends and allow them to perform well. The process of data mining is actually the retrieval process of essential and informative data that helps an organization to analyze the business perspectives and can further generate better interests in cutting cost, developing revenue and to acquire valuable data on business services/products.

It is a powerful analytical tool that permits the user to customize a wide range of data in different formats and categories as per their necessity. The data mining process is an integral part of a business plan for companies that need to undertake a diverse research on the customer building process. These analytical skills are generally performed by skilled industrial experts who assist the firms to accelerate their growth through the critical business activities. With a vast applicability in the present time, the back office support services with the data mining process is helping the businesses in understanding and predicting valuable information. Some of them include:

    Profiles of customers
    Customer buying behavior
    Customer buying trends
    Industry analysis

For a layman it is somewhat the process of processing some statistical data or methods. These processes are implemented with some specific tools that preform the following:

    Automated model scoring
    Business templates
    Computing target columns
    Database integration
    Exporting models to other applications
    Incorporating financial information

There are some benefits of Data Mining. Few of them are as follows:

    To understand the requirements of the customers which can help in efficient planning.
    Helps in minimizing risk and improve ROI.
    Generate more business and target the relevant market.
    Risk free outsourcing experience
    Provide data access to business analysts
    A better understanding of the demand supply graph
    Improve profitability by detect unusual pattern in sales, claims, transactions
    To cut down the expenses of Direct Marketing

Data mining is generally a part of the offshore back office services and outsourced to business establishments that require diverse data base on customers and their particular approach towards any service or product. For example banks, telecommunication companies, insurance companies, etc. require huge data base to promote their new policies. If you represent a similar company that needs appropriate data mining process then it is better that you outsource back office support services from a third party and fulfill your business goals with excellent results.



Source: http://ezinearticles.com/?The-A-B-C-D-of-Data-Mining-Services&id=6503339

Limitations and Challenges in Effective Web Data Mining

Web data mining and data collection is critical process for many business and market research firms today. Conventional Web data mining techniques involve search engines like Google, Yahoo, AOL, etc and keyword, directory and topic-based searches. Since the Web's existing structure cannot provide high-quality, definite and intelligent information, systematic web data mining may help you get desired business intelligence and relevant data.

Factors that affect the effectiveness of keyword-based searches include:
• Use of general or broad keywords on search engines result in millions of web pages, many of which are totally irrelevant.
• Similar or multi-variant keyword semantics my return ambiguous results. For an instant word panther could be an animal, sports accessory or movie name.
• It is quite possible that you may miss many highly relevant web pages that do not directly include the searched keyword.

The most important factor that prohibits deep web access is the effectiveness of search engine crawlers. Modern search engine crawlers or bot can not access the entire web due to bandwidth limitations. There are thousands of internet databases that can offer high-quality, editor scanned and well-maintained information, but are not accessed by the crawlers.

Almost all search engines have limited options for keyword query combination. For example Google and Yahoo provide option like phrase match or exact match to limit search results. It demands for more efforts and time to get most relevant information. Since human behavior and choices change over time, a web page needs to be updated more frequently to reflect these trends. Also, there is limited space for multi-dimensional web data mining since existing information search rely heavily on keyword-based indices, not the real data.

Above mentioned limitations and challenges have resulted in a quest for efficiently and effectively discover and use Web resources. Send us any of your queries regarding Web Data mining processes to explore the topic in more detail.



Source: http://ezinearticles.com/?Limitations-and-Challenges-in-Effective-Web-Data-Mining&id=5012994

How Web Data Extraction Services Will Save Your Time and Money by Automatic Data Collection

Data scrape is the process of extracting data from web by using software program from proven website only. Extracted data any one can use for any purposes as per the desires in various industries as the web having every important data of the world. We provide best of the web data extracting software. We have the expertise and one of kind knowledge in web data extraction, image scrapping, screen scrapping, email extract services, data mining, web grabbing.

Who can use Data Scraping Services?

Data scraping and extraction services can be used by any organization, company, or any firm who would like to have a data from particular industry, data of targeted customer, particular company, or anything which is available on net like data of email id, website name, search term or anything which is available on web. Most of time a marketing company like to use data scraping and data extraction services to do marketing for a particular product in certain industry and to reach the targeted customer for example if X company like to contact a restaurant of California city, so our software can extract the data of restaurant of California city and a marketing company can use this data to market their restaurant kind of product. MLM and Network marketing company also use data extraction and data scrapping services to to find a new customer by extracting data of certain prospective customer and can contact customer by telephone, sending a postcard, email marketing, and this way they build their huge network and build large group for their own product and company.

We helped many companies to find particular data as per their need for example.

Web Data Extraction

Web pages are built using text-based mark-up languages (HTML and XHTML), and frequently contain a wealth of useful data in text form. However, most web pages are designed for human end-users and not for ease of automated use. Because of this, tool kits that scrape web content were created. A web scraper is an API to extract data from a web site. We help you to create a kind of API which helps you to scrape data as per your need. We provide quality and affordable web Data Extraction application

Data Collection

Normally, data transfer between programs is accomplished using info structures suited for automated processing by computers, not people. Such interchange formats and protocols are typically rigidly structured, well-documented, easily parsed, and keep ambiguity to a minimum. Very often, these transmissions are not human-readable at all. That's why the key element that distinguishes data scraping from regular parsing is that the output being scraped was intended for display to an end-user.

Email Extractor

A tool which helps you to extract the email ids from any reliable sources automatically that is called a email extractor. It basically services the function of collecting business contacts from various web pages, HTML files, text files or any other format without duplicates email ids.

Screen scrapping

Screen scraping referred to the practice of reading text information from a computer display terminal's screen and collecting visual data from a source, instead of parsing data as in web scraping.

Data Mining Services

Data Mining Services is the process of extracting patterns from information. Datamining is becoming an increasingly important tool to transform the data into information. Any format including MS excels, CSV, HTML and many such formats according to your requirements.

Web spider

A Web spider is a computer program that browses the World Wide Web in a methodical, automated manner or in an orderly fashion. Many sites, in particular search engines, use spidering as a means of providing up-to-date data.

Web Grabber

Web grabber is just a other name of the data scraping or data extraction.

Web Bot

Web Bot is software program that is claimed to be able to predict future events by tracking keywords entered on the Internet. Web bot software is the best program to pull out articles, blog, relevant website content and many such website related data We have worked with many clients for data extracting, data scrapping and data mining they are really happy with our services we provide very quality services and make your work data work very easy and automatic.


Source: http://ezinearticles.com/?How-Web-Data-Extraction-Services-Will-Save-Your-Time-and-Money-by-Automatic-Data-Collection&id=5159023

Things You Should Know about Data Mining or Data Capturing

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

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

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

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

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

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

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

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



Source: http://ezinearticles.com/?Things-You-Should-Know-about-Data-Mining-or-Data-Capturing&id=256125

Optimize Usage of Twitter With Data Mining

Twitter has become so popular and it is often thought of as very addictive and as more and more people are getting addicted to it, the more Twitter becomes an important medium for driving traffic to your website, marketing your products and services, or for just brand recognition purposes. As an internet marketer, you will always be interested in what's going on inside Twitter but with 40 million people located all over the world, it would be impossible to know it not unless you use additional tools to help you achieve this goal.

Twitter is a microblogging platform that is used by most people to inform their friends and loved ones what is curently going on in them, tweeters can also engaged in some sort of discussions and very recently more and more internet marketers use it to inform everyone about their company, business, products and services.

As an internet marketer, you will need to maximize your usage of Twitter. You may not just only need how to tweet efficiently or how you will be able to broadcast your tweets [http://moneymakingonlinetip.blogspot.com/2010/01/broadcast-your-tweets.html]. You will really need to know the current most talked about topics in twitter on a certain period of time for a certain geographical location. And by knowing this information, you will be able to define a good marketing strategy and how you can blend well with these people. Advertising in the right time and place would promise higher conversion rate translating to higher sales and earning more profits.

This can be achieved with the proper use of Data Mining Tools and Software. There is probably no such tools yet right at this moment, but for sure it will be an excellent strategy to acquire very useful information that will help you succeed in the business generated and extracted form data gathered from Twitter with the help of these Data Mining Tools and Software.




Source: http://ezinearticles.com/?Optimize-Usage-of-Twitter-With-Data-Mining&id=3589673

Data Entry - Unlimited Seats Available For All Data Entry Work

I bet these days many are reading articles giving tips on how to find a job guerrilla style or how to make a hard core resume. After all the number of unemployed has sky rocketed to 15.7 million and the employment field is getting competitive, steeper, opportunities are limited and people are overwhelmed with anxiety to the point that some are losing hope in finding a job. Blood pressures are raising, sugar levels are zooming up and some are punching their calculator like crazy checking how can they stretch the little money left until they found a job (any job will do). Sounds familiar? There is unlimited working opportunity in home based data entry and there is no need for you to worry any further.

The economic crisis has toppled many businesses even businesses that have existed for many generations such as the Lehman Brothers which is a global investment bank was not spared. Businesses resort to massive lay-offs to cut back from overhead costs and stay afloat. In manufacturing, retail and construction many lost their jobs last month. Many companies has employed many strategies to stay afloat and to prevent further lay-offs. Few strategies being employed are unpaid extended vacations, salary freeze, salary cuts, cutting back of working hours, reduction of health plans, unpaid vacations and even mandatory shut downs. Some are even farming out noncore office departments to countries such as India, Singapore and Philippines to take advantage of low labor costs.

With this market condition it is impossible to believe that data entry is recession proof. Data management care is not the heart of business activities. However, customer satisfaction, programming of business plans and strategies and the conceptualization of innovative business ideas all depend on the management of accumulated information gathered by businesses in their day to day operations. Information should be given efficient and careful handling otherwise a business will be compromised. Hence, data care management solutions is very essential to businesses and for as long as there are businesses operating in the country there will always be a need for data management providers. In 2006 there are 948,000 service providers in this occupation and it is still growing in number.

Opportunistic business minded people find this occupation very "green". That is why you will find many fraudulent data entry programs in the internet. We have thousands of data entry jobs available in the country today and it could be full-time or part time job, the money is good and it is open for working mothers, retirees, working dads looking for a part-time job, working students, specially able and even for those who wants to have a full-time home based career.

There are many data entry programs online that you may check if you are truly interested to explore your chances in this occupation. Beware of the hundreds of fraudulent programs proliferating in cyberspace. To save yourself from all the hassle you may try checking the National Data Entry because it is reputed to be legitimate.



Source: http://ezinearticles.com/?Data-Entry---Unlimited-Seats-Available-For-All-Data-Entry-Work&id=3285820

How Data Mining is Useful to Companies?

Every business, organization and government bodies are collecting large amount of data for research and development. Such huge database can make them to have the information on hand when required. But most important is that it takes much time to find important information from the data. "If you want to grow rapidly, you must take quick and accurate decisions to grab timely available opportunities."

By applying the process of data mining, you can easily extract and filter required information from data. It is a processing of refining data and extracting important information. This process is mainly divided into 3 sections; pre-processing, mining and validation. In pre-processing, large amount of relevant data are collected. The mining section includes data classification, clustering, error correction and linking information. The last but important is validate without which you can not make trust on information. In short, data mining is a process of converting data into authentic information.

Let's have look on how data mining is useful to companies.

Fast and Feasible Decisions: To search information from huge bundle of data require more time. It also irritates a person who is doing such. With annoyed mind one can not take accurate decisions that's for sure. By having help of data mining, one can easily get information and make fast decisions. It also helps to compare information with various factors so the decisions become more reliable. Data mining is helpful in every decision to make it quick and feasible.

Powerful Strategies: After data mining, information becomes precise and easy to understand. While making strategies, one can easily analyze information in various dimensions. This analysis helps to get real idea about the strategy implementation. Management bodies can implement powerful strategies effectively to expand business boundaries.

Competitive Advantage: Information is easily available and precise so that one can compare it with competitors' information. It is very much required that you must compare the data otherwise you will have to suffer in business. After doing competitive analysis, one can make corrective decisions to go ahead from competitors. This way company can gain competitive advantage.

Your business can get all the benefits of data mining at cutting rates through outsourcing.


Source: http://ezinearticles.com/?How-Data-Mining-is-Useful-to-Companies?&id=2835042

Unraveling the Data Mining Mystery - The Key to Dramatically Higher Profits

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?


Source: http://ezinearticles.com/?Unraveling-the-Data-Mining-Mystery---The-Key-to-Dramatically-Higher-Profits&id=26665