Data Mining Introduction

We have been "manually" extracting data in relation to the patterns they form for many years but as the volume of data and the varied sources from which we obtain it grow a more automatic approach is required.

The cause and solution to this increase in data to be processed has been because the increasing power of computer technology has increased data collection and storage.

Direct hands-on data analysis has increasingly been supplemented, or even replaced entirely, by indirect, automatic data processing.

Data mining is the process uncovering hidden data patterns and has been used by businesses, scientists and governments for years to produce market research reports. A primary use for data mining is to analyse patterns of behaviour.

It can be easily be divided into stages

Pre-processing

Once the objective for the data that has been deemed to be useful and able to be interpreted is known, a target data set has to be assembled. Logically data mining can only discover data patterns that already exist in the collected data, therefore the target dataset must be able to contain these patterns but small enough to be able to succeed in its objective within an acceptable time frame.

The target set then has to be cleansed. This removes sources that have noise and missing data.

The clean data is then reduced into feature vectors,(a summarized version of the raw data source) at a rate of one vector per source. The feature vectors are then split into two sets, a "training set" and a "test set". The training set is used to "train" the data mining algorithm(s), while the test set is used to verify the accuracy of any patterns found.

Data mining

Data mining commonly involves four classes of task:

    Classification - Arranges the data into predefined groups. For example email could be classified as legitimate or spam.
    Clustering - Arranges data in groups defined by algorithms that attempt to group similar items together
    Regression - Attempts to find a function which models the data with the least error.
    Association rule learning - Searches for relationships between variables. Often used in supermarkets to work out what products are frequently bought together. This information can then be used for marketing purposes.

Validation of Results

The final stage is to verify that the patterns produced by the data mining algorithms occur in the wider data set as not all patterns found by the data mining algorithms are necessarily valid.

If the patterns do not meet the required standards, then the preprocessing and data mining stages have to be re-evaluated. When the patterns meet the required standards then these patterns can be turned into knowledge.


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

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

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

Who Can Benefit From Data Mining Services?

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

How is Raw Data Converted to Useful Information?

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



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Show the Potential of Your Business With Data Entry Services

When you are into a business, every day is like a new challenge for you. You have to do your tasks in a more improved way keeping your business activities maintained. Managing your core activities will help you in building up your business and will also help you to get the best results. Non-core activities will support your core activities in turn enhancing your business. One of the most important non-core activities that get neglected in most of the cases is Data Entry Services. This is one such offshore service that almost all the organizations use. With the increase in popularity, these Services are in high demand these days.

Significance of Data Entry Services

The question is how your data entry services are helping you in achieving your targeted goals and goals? You have to move deeper into the field of these Services to know how exactly these services are helping you. Before we start it is better to know that every business, be it a large-scale business or small-scale, every business produce voluminous amount of data which is very important from business point of view. This is the point where actually the problem starts. Accessing this large volume of data and then analyzing and processing of such a huge amount of data is a difficult task. This work is too much hectic and time-consuming. This is why the organizations are looking for good Data Entry Service to help them organize their data.

Hiring Data Entry Services is beneficial - some points to prove it

1. Low cost: The main benefit of hiring these services is that they will cut their total cost. They offer you the services at lower prices. It is one of the best ways to cut the cost.

2. Professional help: You get direct help from Data Entry Services. You will be given the professionals who have experience from years and will give you correct and proper solutions.

3. Accurate and Fast Services: You are given with fast and correct services as professionals work on your project. These professionals will offer you quick solutions to any of your problems.

4. Security of the data: Organizations are more concerned about their data security because there is an equal competition among the different services. Almost all the service providers offer high security to their customers.

5. More focus on the core activities: With the help of these services, you can concentrate more on your core business. You don't have to worry about managing your data but you can give more attention to your core activities of the business.

6. Comprehensive Advantage: You can enjoy a competitive advantage by concentrating more on your business and spending less on the data management.


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Data Entry Services Make Organizational Functions A Smooth Process

Every organization aims at carrying out its daily processes with clockwork precision. The employees hired in various departments are all specialists in their jobs and the company hopes that the functions will be a smooth flowing process under the supervision and care of these professionals. However there are certain tasks that are mundane in nature but nonetheless are crucial to the existence and profit making capacity of the organization. Data entry of regular processes within the company is one such important aspect of every business. Any organization cannot function smoothly without the requisite data entered and processed accurately and efficiently. Employees are therefore hired to carry out the data entry services which enable the smooth functioning of the business.

Data entry services can be a time consuming task which requires diligent effort of the data entry staff. Each and every transaction needs to be recorded, processed and analyzed to enable the decision makers to have a clear picture of the actual standing of the company. A huge group of people are interested in the data of the company starting from the shareholders to the employees, creditors, consumers and the market in general. Data entry services therefore play a crucial role in determining the present and future of the business and hence this aspect is taken very seriously by every business. Data entry services are now being outsourced from reputed vendors to further simplify the requirements of every business.

Data entry services that are outsourced from vendors help the firm in saving crucial resources which are both human and financial. The data entry services vendor employs qualified professionals to carry out the data entry work for the client. This enables the client to reduce the manpower in the form of salaried staff that was earlier engaged in data entry operations for the firm. This not only leaves the manpower free to be employed in other crucial divisions but also saves on the salary that would otherwise have to be paid to the staff doing data entry services. The vendor generally charges less than what the firm would normally pay to a salaried staff for data entry services and hence it is a win-win situation for all involved.

The data that is collected, recorded, processed helps the company determine the current status of their financial records and the progress made so far. Some firms may not be requiring constant data entry services and for them it makes sense to hire vendors to do the job on a need basis. Meanwhile the firms with permanent data entry requirement can also benefit from a vendor providing regular and up to date data entry services. It would ensure that all information regarding the company data is available at the click of a mouse. Data entry services can be a boon for numerous companies which are dependent on the crucial records of every transaction that takes place within the organization. Now whether the company wants to hire in-house staff or a vendor to take care of data entry services is a matter of convenience and preference but the need for such services will always remain intact and keep growing with the time.




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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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Outsource Data Mining Services to Offshore Data Entry Company

Companies in India offer complete solution services for all type of data mining services.

Data Mining Services and Web research services offered, help businesses get critical information for their analysis and marketing campaigns. As this process requires professionals with good knowledge in internet research or online research, customers can take advantage of outsourcing their Data Mining, Data extraction and Data Collection services to utilize resources at a very competitive price.

In the time of recession every company is very careful about cost. So companies are now trying to find ways to cut down cost and outsourcing is good option for reducing cost. It is essential for each size of business from small size to large size organization. Data entry is most famous work among all outsourcing work. To meet high quality and precise data entry demands most corporate firms prefer to outsource data entry services to offshore countries like India.

In India there are number of companies which offer high quality data entry work at cheapest rate. Outsourcing data mining work is the crucial requirement of all rapidly growing Companies who want to focus on their core areas and want to control their cost.

Why outsource your data entry requirements?

Easy and fast communication: Flexibility in communication method is provided where they will be ready to talk with you at your convenient time, as per demand of work dedicated resource or whole team will be assigned to drive the project.

Quality with high level of Accuracy: Experienced companies handling a variety of data-entry projects develop whole new type of quality process for maintaining best quality at work.

Turn Around Time: Capability to deliver fast turnaround time as per project requirements to meet up your project deadline, dedicated staff(s) can work 24/7 with high level of accuracy.

Affordable Rate: Services provided at affordable rates in the industry. For minimizing cost, customization of each and every aspect of the system is undertaken for efficiently handling work.

Outsourcing Service Providers are outsourcing companies providing business process outsourcing services specializing in data mining services and data entry services. Team of highly skilled and efficient people, with a singular focus on data processing, data mining and data entry outsourcing services catering to data entry projects of a varied nature and type.

Why outsource data mining services?

360 degree Data Processing Operations
Free Pilots Before You Hire
Years of Data Entry and Processing Experience
Domain Expertise in Multiple Industries
Best Outsourcing Prices in Industry
Highly Scalable Business Infrastructure
24X7 Round The Clock Services

The expertise management and teams have delivered millions of processed data and records to customers from USA, Canada, UK and other European Countries and Australia.

Outsourcing companies specialize in data entry operations and guarantee highest quality & on time delivery at the least expensive prices.


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Data Mining - Critical for Businesses to Tap the Unexplored Market

Knowledge discovery in databases (KDD) is an emerging field and is increasingly gaining importance in today's business. The knowledge discovery process, however, is vast, involving understanding of the business and its requirements, data selection, processing, mining and evaluation or interpretation; it does not have any pre-defined set of rules to go about solving a problem. Among the other stages, the data mining process holds high importance as the task involves identification of new patterns that have not been detected earlier from the dataset. This is relatively a broad concept involving web mining, text mining, online mining etc.

What Data Mining is and what it is not?

The data mining is the process of extracting information, which has been collected, analyzed and prepared, from the dataset and identifying new patterns from that information. At this juncture, it is also important to understand what it is not. The concept is often misunderstood for knowledge gathering, processing, analysis and interpretation/ inference derivation. While these processes are absolutely not data mining, they are very much necessary for its successful implementation.

The 'First-mover Advantage'

One of the major goals of the data mining process is to identify an unknown or rather unexplored segment that had always existed in the business or industry, but was overlooked. The process, when done meticulously using appropriate techniques, could even make way for niche segments providing companies the first-mover advantage. In any industry, the first-mover would bag the maximum benefits and exploit resources besides setting standards for other players to follow. The whole process is thus considered to be a worthy approach to identify unknown segments.

The online knowledge collection and research is the concept involving many complications and, therefore, outsourcing the data mining services often proves viable for large companies that cannot devote time for the task. Outsourcing the web mining services or text mining services would save an organization's productive time which would otherwise be spent in researching.

The data mining algorithms and challenges

Every data mining task follows certain algorithms using statistical methods, cluster analysis or decision tree techniques. However, there is no single universally accepted technique that can be adopted for all. Rather, the process completely depends on the nature of the business, industry and its requirements. Thus, appropriate methods have to be chosen depending upon the business operations.

The whole process is a subset of knowledge discovery process and as such involves different challenges. Analysis and preparation of dataset is very crucial as the well-researched material could assist in extracting only the relevant yet unidentified information useful for the business. Hence, the analysis of the gathered material and preparation of dataset, which also considers industrial standards during the process, would consume more time and labor. Investment is another major challenge in the process as it involves huge cost on deploying professionals with adequate domain knowledge plus knowledge on statistical and technological aspects.

The importance of maintaining a comprehensive database prompted the need for data mining which, in turn, paved way for niche concepts. Though the concept has been present for years now, companies faced with ever growing competition have realized its importance only in the recent years. Besides being relevant, the dataset from where the information is actually extracted also has to be sufficient enough so as to pull out and identify a new dimension. Yet, a standardized approach would result in better understanding and implementation of the newly identified patterns.


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Data Mining's Importance in Today's Corporate Industry

A large amount of information is collected normally in business, government departments and research & development organizations. They are typically stored in large information warehouses or bases. For data mining tasks suitable data has to be extracted, linked, cleaned and integrated with external sources. In other words, it is the retrieval of useful information from large masses of information, which is also presented in an analyzed form for specific decision-making.

Data mining is the automated analysis of large information sets to find patterns and trends that might otherwise go undiscovered. It is largely used in several applications such as understanding consumer research marketing, product analysis, demand and supply analysis, telecommunications and so on. Data Mining is based on mathematical algorithm and analytical skills to drive the desired results from the huge database collection.

It can be technically defined as the automated mining of hidden information from large databases for predictive analysis. Web mining requires the use of mathematical algorithms and statistical techniques integrated with software tools.

Data mining includes a number of different technical approaches, such as:

    Clustering
    Data Summarization
    Learning Classification Rules
    Finding Dependency Networks
    Analyzing Changes
    Detecting Anomalies

The software enables users to analyze large databases to provide solutions to business decision problems. Data mining is a technology and not a business solution like statistics. Thus the data mining software provides an idea about the customers that would be intrigued by the new product.

It is available in various forms like text, web, audio & video data mining, pictorial data mining, relational databases, and social networks. Data mining is thus also known as Knowledge Discovery in Databases 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 therefore has arrived on the scene at the very appropriate time, helping these enterprises to achieve a number of complex tasks that would have taken up ages but for the advent of this marvelous new technology.


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Data Mining Is Useful for Business Application and Market Research Services

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

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

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

Benefits of Data mining services in Business

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

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

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


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Outsourcing And Archiving Your Data

Whether a company relies heavily on database activity for critical everyday business operations or only for select requirements, the loss of data due to technological failure can have far reaching negative implications. The loss of valuable information and records can cause productivity setbacks, lost profits, lost customers, and headaches for everyone involved. Aside from the obvious business challenges associated with the loss of data, legislation such as the Sarbanes-Oxley Act (SOX) places requirements on the retention and provision of certain types of financial data. Companies assume the risk of non-compliance if they are unable to produce information within the specified time constraint required by Sarbanes-Oxley (SOX) or other information-focused legislation. Database and mainframe disaster recovery is more important in today¹s technology dependent business world than ever before.

When it comes to archiving your company¹s data, the advantages of archiving your information with an outside source include:

o Fast and straightforward deployment with no large out-of-pocket initial expenses.

o If customers don't like the service, they can simply decline renewing their contract (which usually runs for one to three years), rather than worry about the unwanted hardware and software sitting on their premises.

o Outsourcing is great for companies with no IT department, or a small or overstretched IT department. The service provider handles all heavy-duty aspects of administration, while the customer is left with relatively few tasks.

o By and large, outsourcers are always up-to-date with the latest releases and versions of hardware and software. The upgrade process is more painful and expensive in-house.

o Scalability and dispersed geographic locations can be more easily accommodated by outsourcers than through in-house installations.

Ever increasing data retention requirements have placed monumental pressure on companies, as the software for archiving must be extremely advanced with tremendous capacities and prolonged reliability.

Outsourcing your archival data saves time and money and reduces the risk and complexity of keeping up with such demands. Are there cons to having to outsource your archives? Possibly, but certainly not compared to the value.


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Some of the Main Techniques For Data Mining

Data mining is the process of extracting relationships from large data sets. It is an area of Computer Science that has received significant commercial interest. In this article I will detail a few of the most common methods of data mining analysis.

Association rule discovery: Association rule discovery methods are used to extract associations from data sets. Traditionally, the technique was developed on supermarket purchase data. An association rule is a rule of the form X -> Y. An example of this may be "If a customer purchases milk this implies (->) that the customer will also purchase bread". An association rule has associated with it a support and a confidence value. The support is the percentage of all entries (or transactions in this case) that have all the items. For example, the percentage of all transactions in which milk and bread were purchased. The confidence is the percentage of the transactions that satisfy the left hand side of the rule that also satisfy the right hand side of the rule. For example, in this case, the confidence would be the percentage of purchases that purchased milk which also purchased bread. Association discovery methods will extract all possible association rules from a data set for which the user has specified a minimum support and confidence.

Cluster Analysis: Cluster analysis is the process of taking one or more numerical fields and assigning clusters their values. These clusters represent groups of points which are close to each other. For example, if you watch a documentary on space, you will see that galaxies contain a lot of stars and planets. There are many galaxies in space, however the stars and planets all occur in clusters that are the galaxies. That is, the stars and planets are not randomly located in space but are clumped together in groups that are galaxies. A cluster analysis method is used to find these sorts of groups. If a cluster analysis method was applied to the stars in space, it may find that each galaxy is a cluster and assign a unique cluster identification to each star in a given galaxy. This cluster identification then becomes another field in the data set and can be used in further data mining analysis. For example, you might use a cluster id field to form association rules to other fields in the data set.

Decision Trees: Decision trees are used to form a tree of decisions in a data set to help predict a value. For example, if you were looking at a data set that was used to predict weather a potential loan applicant would be a credit risk, a tree of decisions would be formed based on factors in the data set. The tree may contain decisions such as whether the applicant had defaulted on a loan before, the age of the applicant, whether the applicant was employed or not, the applicants income and the total repayments on the loan. You could then follow this tree of decisions to say for example, if an applicant has never defaulted on a loan before, the applicant is employed, their income is in the top 15 percentile for the country and the loan amount relatively low then there is a very low risk of default.

These are some of the more common techniques for data mining analysis amongst a large group of data mining techniques that a commonly applied to analyzing large data sets. These techniques have proved beneficial to gather useful information and relationships from data that may otherwise be too large to interpret well.



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Data Mining vs Screen-Scraping

Data mining isn't screen-scraping. I know that some people in the room may disagree with that statement, but they're actually two almost completely different concepts.

In a nutshell, you might state it this way: screen-scraping allows you to get information, where data mining allows you to analyze information. That's a pretty big simplification, so I'll elaborate a bit.

The term "screen-scraping" comes from the old mainframe terminal days where people worked on computers with green and black screens containing only text. Screen-scraping was used to extract characters from the screens so that they could be analyzed. Fast-forwarding to the web world of today, screen-scraping now most commonly refers to extracting information from web sites. That is, computer programs can "crawl" or "spider" through web sites, pulling out data. People often do this to build things like comparison shopping engines, archive web pages, or simply download text to a spreadsheet so that it can be filtered and analyzed.

Data mining, on the other hand, is defined by Wikipedia as the "practice of automatically searching large stores of data for patterns." In other words, you already have the data, and you're now analyzing it to learn useful things about it. Data mining often involves lots of complex algorithms based on statistical methods. It has nothing to do with how you got the data in the first place. In data mining you only care about analyzing what's already there.

The difficulty is that people who don't know the term "screen-scraping" will try Googling for anything that resembles it. We include a number of these terms on our web site to help such folks; for example, we created pages entitled Text Data Mining, Automated Data Collection, Web Site Data Extraction, and even Web Site Ripper (I suppose "scraping" is sort of like "ripping"). So it presents a bit of a problem-we don't necessarily want to perpetuate a misconception (i.e., screen-scraping = data mining), but we also have to use terminology that people will actually use.



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Data Entry Outsourcing

Data entry outsourcing provides a tremendous amount of flexibility in budget because offsite data entry outsourcing services enable organizations to pay for certain services on a per project and as needed basis. The option cuts down costs and need for hiring special personnel and training them, harnessing fresh engineering proficiency, and slashes the expenditure to be made on operations. In general such tasks tend to be repetitive and monotonous yet require a high degree of attention to detail. For these reasons and more, most businesses choose to outsource such tasks to specialists.

The effectiveness of employing freelance staff members at a preferred rate was gaining momentum even among businesses operating on a small scale. Data entry outsourcing of specific tasks to outsiders meant that organizations could make use of the know-how possessed by them, even though the organization did not have offices in those parts of the globe.

Data entry outsourcing projects are growing exponentially, in terms of the revenues involved, people employed, and the amount of data entailed. With the world going digital, the speed and accuracy is greatly enhanced when companies decide to outsource such tasks. The service providers and service buyers can now function almost on a real-time basis, although they may be geographically poles apart. This leads to the leveraging of scale of the economy of the outsourced work and the capacity to deliver astronomically valuable service at reduced, end-customer price.

The size of the database of all businesses is expanding. The strategic or top management is able to project into the future using the data of the past. Data is a managerial tool. As it is difficult to house every procedure under one roof, the importance of data entry outsourcing is in high demand. Much stress can be taken away, and the venture turned profitable, especially if the low-cost, third world countries are targeted.

Data entry outsourcing may typically call for online or offline treatment at the providers' end. It is a lucrative and astute choice to outsource the entering of data because the business going in for it can focus on core processes, leaving the work of entering data to reliable service providers - those who specialize in the field and have the necessary infrastructure. Businesses, which outsource data entry to self owned or third-party service providers, have been found to do financially better than others. This results in their being able to pay their workers higher wages and influence their morale positively.


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Data Mining: Its Description and Uses

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

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

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

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

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

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

Generally, any of the following relationships are obtained.

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


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Data Mining and the Tough Personal Information Privacy Sell Considered

Everyone come on in and have a seat, we will be starting this discussion a little behind schedule due to the fact we have a full-house here today. If anyone has a spare seat next to them, will you please raise your hands, we need to get some of these folks in back a seat. The reservations are sold out, but there should be a seat for everyone at today's discussion.

Okay everyone, I thank you and thanks for that great introduction, I just hope I can live up to all those verbal accolades.

Oh boy, not another controversial subject! Yes, well, surely you know me better than that by now, you've come to expect it. Okay so, today's topic is one about the data mining of; Internet Traffic, Online Searches, Smart Phone Data, and basically, storing all the personal data about your whole life. I know, you don't like this idea do you - or maybe you participate online in social online networks and most of your data is already there, and you've been loading up your blog with all sorts of information?

Now then, contemporary theory and real world observation of the virtual world predicts that for a fee, or for a trade in free services, products, discounts, or a chance to play in social online networks, employment opportunity leads, or the prospects of future business you and nearly everyone will give up some personal information.

So, once this data is collected, who will have access to it, who will use it, and how will they use it? All great questions, but first how can the collection of this data be sold to the users, and agreed upon in advance? Well, this can at times be very challenging; yes, very tough sell, well human psychology online suggests that if we give benefits people will trade away any given data of privacy.

Hold That Thought.

Let's digress a second, and have a reality check dialogue, and will come back to that point above soon enough, okay - okay agreed then.

The information online is important, and it is needed at various national security levels, this use of data is legitimate and worthy information can be gained in that regard. For instance, many Russian Spies were caught in the US using social online networks to recruit, make business contacts, and study the situation, makes perfect sense doesn't it? Okay so, that particular episode is either; an excuse to gather this data and analyze it, or it is a warning that we had better. Either way, it's a done deal, next topic.

And, there is the issue with foreign spies using the data to hurt American businesses, or American interests, or even to undermine the government, and we must understand that spies in the United States come from over 70 other nations. And let's not dismiss the home team challenge. What's that you ask? Well, we have a huge intelligence industrial complex and those who work in and around the spy business, often freelance on the side for Wall Street, corporations, or other interests. They have access to information, thus all that data mined data is at their disposal.

Is this a condemnation of sorts; No! I am merely stating facts and realities behind the curtain of created realities of course, without judgment, but this must be taken into consideration when we ask; who can we trust with all this information once it is collected, stored, and in a format which can be sorted? So, we need a way to protect this data for the appropriate sources and needs, without allowing it to be compromised - this must be our first order of business.

Let's Undigress and Go Back to the Original Topic at hand, shall we? Okay, deal.

Now then, what about large corporate collecting information; Proctor and Gamble, Ford, GM, Amazon, etc? They will certainly be buying this data from social networks, and in many cases you've already given up your rights to privacy merely by participating. Of course, all the data will help these companies refine their sorts using your preferences, thus, the products or services they pitch you will be highly targeted to your exact desires, needs, and demographics, which is a lot better than the current bombardment of Viagra Ads with disgusting titles, now in your inbox, deleted junk files.

Look, here is the deal...if we are going to collect data online, through social networks, and store all that the data, then we also need an excuse to collect the data first place, or the other option is not tell the public and collect it anyway, which we already probably realize that is now being done in some form or fashion. But let's for the sake of arguments say it isn't, then should we tell the public we are doing, or are going to do this. Yes, however if we do not tell the public they will eventually figure it out, and conspiracy theories will run rampant.

We already know this will occur because it has occurred in the past. Some say that when any data is collected from any individual, group, company, or agency, that all those involved should also be warned on all the collection of data, as it is being collected and by whom. Including the NSA, a government, or a Corporation which intends on using this data to either sell you more products, or for later use by their artificial intelligence data scanning tools.

Likewise, the user should be notified when cookies are being used in Internet searchers, and what benefits they will get, for instance; search features to help bring about more relevant information to you, which might be to your liking. Such as Amazon.com which tracks customer inquiries and brings back additional relevant results, most online shopping eCommerce sites do this, and there was a very nice expose on this in the Wall Street Journal recently.

Another digression if you will, and this one is to ask a pertinent question; If the government or a company collects the information, the user ought to know why, and who will be given access to this information in the future, so let's talk about that shall we? I thought you might like this side topic, good for you, it shows you also care about these things.

And as to that question, one theory is to use a system that allows certain trusted sources in government, or corporations which you do business with to see some data, then they won't be able to look without being seen, and therefore you will know which government agencies, and which corporations are looking at your data, and therefore there will be transparency, and there would have to be at that point justification for doing so. Or most likely folks would have a fit and then, a proverbial field day with the intrusion in the media.

Now then, one recent report from the government asks the dubious question; "How do we define the purpose for which the data will be used?"

Ah ha, another great question in this on-going saga indeed. It almost sounds as if they too were one of my concerned audience members, or even a colleague. Okay so, it is important not only to define the purpose of the data collection, but also to justify it, and it better be good. Hey, I see you are all smiling now. Good, because, it's going to get a bit more serious on some of my next points here.

Okay, and yes this brings about many challenges, and it is also important to note that there will be, ALWAYS more outlets for the data, which is collected, as time goes on. Therefore the consumer, investor, or citizen who allows their data to be compromised, stored for later use for important issues such as national security, or for corporations to help the consumer (in this case you) in their purchasing decisions, or for that company's planning for inventory, labor, or future marketing (most likely; again to whom; ha ha ha, yes you are catching on; You.

Thus, shouldn't you be involved at every step of the way; Ah, a resounding YES! I see from our audience today, and yes, I would have expected nothing less from you either. And as all this process takes place, eventually "YOU" are going to figure out that this data is out of control, and ends up everywhere. So, should you give away data easily?

No, and if it is that valuable, hold out for more. And then, you will be rewarded for the data, which is yours, that will be used on your behalf and potentially against you in some way in the future; even if it is only for additional marketing impressions on the websites you visit or as you walk down the hallway at the mall;

"Let's see a show of hands; who has seen Minority Report? Ah, most of you, indeed, if you haven't go see, it and you will understand what we are all saying up here, and others are saying in the various panel discussions this weekend."

Now you probably know this, but the very people who are working hard to protect your data are in fact the biggest purveyors of your information, that's right our government. And don't get me wrong, I am not anti-government, just want to keep it responsible, as much is humanly possible. Consider if you will all the data you give to the government and how much of that public record is available to everyone else;

    Tax forms to the IRS,
    Marriage licenses,
    Voting Registration,
    Selective Services Card,
    Property Taxes,
    Business Licenses,
    Etc.

The list is pretty long, and the more you do, the more information they have, and that means the more information is available; everywhere, about who; "YOU! That's who!" Good I am glad we are all clear on that one. Yes, indeed, all sorts of things, all this information is available at the county records office, through the IRS, or with various branches of OUR government. This is one reason we should all take notice to the future of privacy issues. Often out government, but it could be any first world government, claims it is protecting your privacy, but it has been the biggest purveyors of giving away our personal and private data throughout American history. Thus, there will a little bit of a problem with consumers, taxpayers, or citizens if they no longer trust the government for giving away such things as;

    Date of birth,
    Social Security number,
    Driver's license,
    Driving record,
    Taxable information,
    Etc., on and on.

And let's not kid ourselves here all this data is available on anyone, it's all on the web, much of it can be gotten free, some costs a little, never very much, and believe me there is a treasure trove of data on each one of us online. And that's before we look into all the other information being collected now.

Now then, here is one solution for the digital data realm, including smart phone communication data, perhaps we can control and monitor the packet flow of information, whereby all packets of info is tagged, and those looking at the data will also be tagged, with no exceptions. Therefore if someone in a government bureaucracy is looking at something they shouldn't be looking at, they will also be tagged as a person looking for the data.

Remember the big to do about someone going through Joe The Plumber's records in OH, or someone trying to release sealed documents on President Bush's DUI when he was in his 20s, or the fit of rage by Sara Palin when someone hacked her Yahoo Mail Account, or when someone at a Hawaii Hospital was rummaging through Barak Obama's certificate of showing up at the hospital as a baby, with mother in tow?

We need to know who is looking at the data, and their reason better be good, the person giving the data has a right-to-know. Just like the "right-to-know" laws at companies, if there are hazardous chemicals on the property. Let me speak on another point; Border Security. You see, we need to know both what is coming and going if we are to have secure borders.

You see, one thing they found with our border security is it is very important not only what comes over the border, which we do need to monitor, but it's also important to see what goes back over the border the other way. This is how authorities have been able to catch drug runners, because they're able to catch the underground economy and cash moving back to Mexico, and in holding those individuals, to find out whom they work for - just like border traffic - our information goes both ways, if we can monitor for both those ways, it keeps you happier, and our data safer.

Another question is; "How do we know the purpose for data being collected, and how can the consumer or citizen be sure that mass data releases will not occur, it's occurred in almost every agency, and usually the citizens are warned that their data was released or that the data base containing their information was breached, but that's after the fact, and it just proves that data is like water, and it's hard to contain. Information wants to be free, and it will always find a way to leak out, especially when it's in the midst of humans.

Okay, I see my time is running short here, let me go ahead and wrap it up and drive through a couple main points for you, then I'll open it up for questions, of which I don't doubt there will be many, that's good, and that means you've been paying attention here today.

It appears that we need to collect data for national security purposes research, planning, and for IT system for future upgrades. And collecting data for upgrades of an IT system, you really need to know about the bulk transfers of data and the time, which that data flows, and therefore it can be anonymized.

For national security issues, and for their research, that data will have anomalies in it, and there are problems with anomalies, because can project a false positives, and to get it right they have to continually refine it all. And although this may not sit well with most folks, nevertheless, we can find criminals this way, spies, terrorist cells, or those who work to undermine our system and stability of our nation.

With regards to government and the collection of data, we must understand that if there are bad humans in the world, and there are. And if many of those who shall seek power, may not be good people, and since information is power, you can see the problem, as that information and power will be used to help them promote their own agenda and rise in power, but it undermines the trust of the system of all the individuals in our society and civilization.

On the corporate front, they are going to try to collect as much data on you as they can, they've already started. After all, that's what the grocery stores are doing with their rewards program if you hadn't noticed. Not all the information they are collecting they will ever use, but they may sell it to third part affiliates, partners, or vendors, so that's at issue. Regulation will be needed in this regard, but the consumer should also have choices, but they ought to be wise about those choices and if they choose to give away personal information, they should know the risks, rewards, consequences, and challenges ahead.

Indeed, I thank you very much, and be sure to pick up a handout on your way out, if you didn't already get one, from the good looking blonde, Sherry, at the door. Thanks again, and let's take a 5-minute break, and then head into the question and answer session, deal?



Source: http://ezinearticles.com/?Data-Mining-and-the-Tough-Personal-Information-Privacy-Sell-Considered&id=4868392

Innovative Online Data Entry Services

Number of companies providing data entry services has increased in the last few years. These companies also provide services on online and offline data-entry and data processing, etc. Data Entry is to enter any form of data into computerized inventory. It could be done by typing at a keyboard plus electronically entering information into the machine.

These companies have updated technologies, unique processes and efficient data processing by integrating skilled professionals. These companies deliver high-quality services with complete accuracy, efficiency plus effectiveness. They provide services through reliable and secure online platform with the help of encrypted FTP upload CD-R or CD-W or E-mail. Adopting this technology customers get an assurance that their information is free from any sort of unauthorized access, copying or downloading. Companies specializing in such services provide a broad spectrum of services fulfilling each customer specific needs.

Few of these services are listed as follows: surveys, online copying, pasting, sorting, editing, and organizing data, questionnaires, online form processing and filing, reports and submissions, online medical and legal data entry, data collection, mailing list / mailing label, email mining, typing the manuscript in MS Word, etc. Outsourcing of the documentation of the work is a workable and a reasonable option.

Such services includes a wide range of back office and BPO - Business Process Outsourcing and ITO - Information Technology Outsourcing enabled data processing services.

Online data input services provided by India have earned a global recognition for its superior quality and timely completion of its work. Saving time is crucial for each organization running its business. Qualitative output is produced in lesser time which is advantageous for using the time at other important places. By availing such services one can save on cost of hiring trained professionals. More services could be availed within the saved cost.

Talking about the role of online data processing services, as the requirements of high quality and accurate data-entry of textual and numeric data processing business needs is most needed. In this way, companies can save valuable time and money by entering information online reduces. You can also consult experts who have vast experience and knowledge about online entry of data.

With the help of these services, mostly many business processing companies are able to focus on their core activates through online services. This kind of services require speed, analytical skills, domain expertise and industry experience. Choosing right outsourcing partner can save you cost and time significantly.


Source: http://ezinearticles.com/?Innovative-Online-Data-Entry-Services&id=6442656

Data Entry Outsourcing Is For Companies That Want To Ease Off Workload

Data entry is not everyone's job; you need people who are technically qualified to do the job for you. Data entry is one of the common sources for which outsourcing are done on a large scale. To an average person, this may appear to be a thing that can be done easily without any special effort. But doing this job can be very tiring, time consuming and may also require huge amounts of money, so data entry outsourcing is an option that business owners or other professionals can explore. Data entry outsourcing is not just about entering information on certain aspects, but also about lessening the workload on other professionals.

Data entry is the process of feeding data or information to the database of spreadsheets. There are two ways of doing data entry to the database. One is that process where the entry is done manually while the other is the process where it is done automatically by a machine. There are many people who prefer using the automated process of data entry, as they find this to be more suitable for them. Nonetheless, each form of data entry has its own advantages and disadvantages.

Data entry outsourcing works out to be beneficial in two ways. First, the company that is outsourcing the work saves huge amounts of money, since the work will be done at a low cost. Also the company that is doing the work will be benefited as they will do the work at a cheaper rates compared to others and the amount they have to spend for doing the work is low. So if a process works out to the advantage of two parties, then this is certainly a good way of doing business. Data entry outsourcing is being undertaken on a very large scale these days.

That is not all; data entry outsourcing enables you to get your work done from professionals who are highly qualified. This is the reason why there is very little chance of anything going wrong with your data entry outsourcing work. Also all outsourcing work is under strict security, so there is no chance of your data falling to the wrong hands and then being used for any fraudulent purposes. All the different aspects are taken care of by third parties that do the outsourcing work, so data entry outsourcing is a safe option for you to invest in.

Data entry can be of different type and used for different purposes. It can be for entering visitor's data for a website, data for keeping track of credit card and debit card transactions, processing and submitting of forms that are filled out online by visitors, creating a database for emailing and also entering images in different format for different purposes. You may need to enter numeric data, alphabetic data, alpha numeric data and text data. Whatever type of data you may need to enter, the baseline is that data entry outsourcing will surely work favorably for you.


Source: http://ezinearticles.com/?Data-Entry-Outsourcing-Is-For-Companies-That-Want-To-Ease-Off-Workload&id=415907