Customer Relationship Management (CRM) Using Data Mining Services

In today's globalized marketplace Customer relationship management (CRM) is deemed as crucial business activity to compete efficiently and outdone the competition. CRM strategies heavily depend on how effectively you can use the customer information in meeting their needs and expectations which in turn leads to more profit.

Some basic questions include - what are their specific needs, how satisfied they are with your product or services, is there a scope of improvement in existing product/service and so on. For better CRM strategy you need a predictive data mining models fueled by right data and analysis. Let me give you a basic idea on how you can use Data mining for your CRM objective.

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

Let me explain last three steps in detail.

Visualize a Model:
Building a predictive data model is an iterative process. You may require 2-3 models in order to discover the one that best suit your business problem. In searching a right data model you may need to go back, do some changes or even change your problem statement.

In building a model you start with customer data for which the result is already known. For example, you may have to do a test mailing to discover how many people will reply to your mail. You then divide this information into two groups. On the first group, you predict your desired model and apply this on remaining data. Once you finish the estimation and testing process you are left with a model that best suits your business idea.

Explore Model:
Accuracy is the key in evaluating your outcomes. For example, predictive models acquired through data mining may be clubbed with the insights of domain experts and can be used in a large project that can serve to various kinds of people. The way data mining is used in an application is decided by the nature of customer interaction. In most cases either customer contacts you or you contact them.

Set up Model & Start Monitoring:
To analyze customer interactions you need to consider factors like who originated the contact, whether it was direct or social media campaign, brand awareness of your company, etc. Then you select a sample of users to be contacted by applying the model to your existing customer database. In case of advertising campaigns you match the profiles of potential users discovered by your model to the profile of the users your campaign will reach.

In either case, if the input data involves income, age and gender demography, but the model demands gender-to-income or age-to-income ratio then you need to transform your existing database accordingly.



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Advantages of Data Mining in Various Businesses

Data mining techniques have advantages for several types of businesses, as well as there are more to be discovered over time. Since the era of the computer, things have been changing pretty quickly and every new step in the technology is equivalent to a revolution. Communication itself has not been enough. As compared to the present times, the data analyzers in the past have not achieved the chance to go further with the data they have in hand. Today, this data isn't used for selling more of a product but to foresee future risks as well as prevent them.

All are benefiting from modern these techniques even from smaller to large enterprises. They can now predict the outcome of a particular marketing campaign by analyzing them. However, in order for these techniques to be successful, the data must be arranged accurately. If your data is disseminated, you need to bring it in a meeting and then feed into the systems for the algorithms to figure it out. To put it shortly, no matter how small or big your business might be you always need to have the right system when collecting data from your customers, transactions and all business activities.

Advantages of Data Mining For Businesses

Businesses can truly benefit from its latest techniques; however, in the future, data mining techniques are expected to be even more concise and effective than they are today. Here are the essential techniques that you need to understand:

· Big companies providing the free web based email services can use data mining techniques to catch spam emails from their customer's inboxes. Their software uses a technique to assess whether an email is a spam or not. These techniques are first tested and validated before they are finally used. This is to ensure they are producing the correct results.

· Large retail stores and even shopping malls could make use of these techniques by registering and recording the transactions made by their customers. When customers are buying particular sets of product, it can give them a good understanding of placing these items in the aisle. If they want to change the order and placement of the item on weekends, it could be found out after analyzing the data on their database.

· Companies manufacturing edible or drinkable products could easily use data mining techniques to increase their sales in a particular area and launch new products based on the information they've obtained. That's why the conventional statistical analysis is rigid in scenarios wherein consumer behavior is in question. However, these techniques still manages to give you good analysis for any situations.

· In call centers, the human interaction is at its peak because people are talking with another people at all times. Customers respond differently when they talk to a female representative as opposed to talking to a male representative. The response of customers to an infomercial is different from their response to an ad in the newspaper. Data could be used for the benefit of the business and is best understood with the use of data mining techniques.

· Data mining techniques are also being used in sports today for analyzing the performances of players in the field. Any game could be analyzed with the help of these techniques; even the behaviors of players could be changed on the field through this.

In short, data mining techniques are giving the organizations, enterprises and smaller businesses the power of focusing on their most productive areas. These techniques also allow stores and companies to innovate their current selling techniques by unveiling the hidden trends of their customer's behavior, background, price of the products, placement, closeness to the related products and many more.



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Outsource Data Entry

Need to outsource data entry? It may seem like an easy task, but most businesses outsource data entry tasks. As the number of companies and firms grow, more and more job opportunities for such service providers are opening up. The first step to outsource these tasks is to identify the scope of the job that you want to outsource. This means figuring out exactly what you want the person you will be hiring to do for you. The service provider can help too and will ask if anything is unclear.

The job could be for the finance department which would deal with handling expenses and incomes, or it could be for the Human Resource Department handling the data base of employees and keeping it updates according to new additions or people who leave. Once, the scope of the job has been finalized, the data needs to be assembled. This could be in the form of sheets of paper that contain bills, details of expenses and various other types of tabulated data, both online and offline.

Since the work is so varied and vast, most businesses choose to outsource data entry projects. This can be done by hiring a company, BPO's or by hiring an individual to do the work for them. BPO's have entire teams that specialize in different forms of such tasks and are fluent in working with the many software out there available. There are different advantages to using companies or individuals to outsource data entry work. While individuals have the benefit of being a little bit more flexible when it comes to demands and specifications, companies that work towards performing entry tasks are more efficient and better time managers due to the vast number of people they hire and train to do the job.

When deciding to outsource the data entry task, care must be taken to ensure that the business you are contacting is legitimate and has the means or manpower necessary to perform the task, particularly if you have special software in place just for entering and organizing data. No matter what kind of data you are handing over, be it in the form of sheets of pages that need to be converted into tables, photographs of papers or maybe an audio transcription needs to be done, companies that deal with data entry tasks are capable of handling all kinds of data and converting and tabulating them into any form you want.




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Control Your Data Entry Cost

I am sure all will agree that a company's main motto would be to boost up the revenue and to derogate the expenses, to save time and to focus on the core business. For maintaining the data of the company with the all above can be achieved by using outsourcing method. The main benefits of outsourcing are cost effectiveness. This is brought about by the reduction in man power, infrastructure, investments on technologies and software.

Offshore outsourcing is still more cost effective as same benefits are obtained with the same quality level at much lower cost. It reduces the burden of standardizing the infrastructure and updating the software needed for the data maintenance by the company itself. Outsourcing improves the productivity level with quality and greatly changes the magnitude of profit level. The cut off of salary for the professional man power to maintain the data is the best cost control for a company. The capital investment is saved by removing off the expenditure for unnecessary fixed investments.

The best benefit from outsourcing can be obtained by choosing an outsourcing partner who is specifically specialized in particular business process. In this case the partner will be able to give out more proficient and good quality services. It also provides faster deliverables. Countries like U.S, U.K benefit the best out of outsourcing in offshore countries like India as they have the zone advantage. During the off time of the office, any critical work is done by the outsourcing partner and hence gives the business a competitive advantage.

Data Entry Services - VServe Solution provides services such as data entry, data capture, data processing, document management and data transcription.




Source: http://ezinearticles.com/?Control-Your-Data-Entry-Cost&id=2375184

Online Data Entry Services

Online data entry services are now commonly used by businesses and these services are generally offered by outsourcing companies with the required standards and specifications. As everything is becoming global, business entities need to manage their valuable and critical data in an accurate and organized manner in order to maintain their competitiveness in the global marketplace. They usually entrust their non core, repetitive and other support tasks to BPO firms who can offer affordable, reliable and trustworthy documentation services online.

Online data entry services have become immensely helpful in all fields where the data needs to be stored, maintained and used for future applications. Today, many firms have partnered with business process outsourcing companies to have an excellent data management system in their facilities. By integrating state-of-the-art technologies, unique processes and skilled data entry specialists, these firms deliver data entry services with accuracy, efficiency and effectiveness. They offer their services through safe and secure online platform. They deliver the final outputs in encrypted FTP upload, CD-R or CD-W or email. Thus, clients are assured that their data or information is free from unauthorized access, copying or downloading.

Business process outsourcing companies specializing in online data entry services offer a wide spectrum of services, tailored to the particular needs of each client. Some of them are listed below:

o Text, numeric or alphanumeric, image or hardcopy date entry
o Data entry from handwritten or printed materials such as books, newspapers, magazines
o Catalog and business card documentation
o E-books and e-magazines
o Data entry from insurance claims and property tax records
o Online listing of yellow pages
o For website content
o Documentation of surveys, questionnaires, company reports and airway bill entries
o Data capture/collection
o Online form processing and submission
o For mailing list/mailing label
o Email mining
o Typing manuscript into MS Word
o Online copying, pasting, editing, sorting, and indexing data
o Online medical and legal data entry
o Data entry of historical data

Outsourcing your documentation task to a BPO firm is a viable and economical choice. You can eliminate tedious and time consuming tasks from your regular routine. As data entry services are developing in tune with the giant leaps in technology, your firm can also utilize these services and stay competitive in the field. Moreover, you can reduce costs, improve productivity and give more importance to core and revenue generating functions.



Source: http://ezinearticles.com/?Online-Data-Entry-Services&id=1523796

Data Mining and Financial Data Analysis

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

Objective:

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

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

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

Data mining:

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

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

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

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

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

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

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

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

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

Data Warehouse:

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

Text:

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

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

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

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

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

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

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

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

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

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

The Products:

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

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

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

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

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

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

ProfitSystem fx Profit Driver by CCH Tax and Accounting provides a wide range of financial diagnostics and analytics. It provides data in spreadsheet form and can calculate benchmarking against industry standards. The program can track up to 40 periods.



Source: http://ezinearticles.com/?Data-Mining-and-Financial-Data-Analysis&id=2752017

New Method of Market Segmentation - Combining Segmentation With Data Mining

Marketers have the ability to get high-fidelity information on their target markets through market segmentation. Market segmentation is the process of categorizing potential customers based on certain variables, such as age, gender, and income. A market segment is a group of customers that will react in the same way to a particular marketing campaign. By gathering this information, marketers can tailor their campaigns to groups of prospects to build stronger relationships with them.

Marketers gather this demographic information through surveys, usually when the customer submits a product rebate or willingly participates in a customer satisfaction survey. Over the majority of the past few decades, market segmentation consisted of differentiating prospects based on very simple variables: income, race, location, etc. While this is definitely important information to have on your target market, modern market segmentation takes into account more integrated information.

Modern segmentation breaks the market into target clusters that take into account not only standard demographics, but also other factors such as population density, psychographics, and buying and spending habits of customers. By focusing on these variables in addition to standard demographics, you can gain deeper insight into customer behavior.

Using standard demographics, you can tailor your marketing pieces to specific groups of people. But, by including these more sophisticated variables in your segmentation process, you can determine achieve a higher degree of "lift" or return on your segmentation efforts.

Segmenting your market on these factors helps you realize your total opportunity and revenue potential. It can enable you to better compete with similar product or service providers and lets you know where you stand within the game. It can help you target untapped market opportunities and allow you to better reach and retain customers.

Market segmentation depends on the gathering of high-quality, usable data. Many companies exist to gather and sell massive databases of targeted customer information, as well as providing consultation services to help you make sense of data bought or already owned. The key to the process is determining the best way to split up data.

There are essentially two methods for categorizing customers. Segments can either be determined in advance and then customers are assigned to each segment, or the actual customer data can be analyzed to identify naturally occurring behavioral clusters. Each cluster forms a particular market segment.

The benefit of cluster-based segmentation is that as a market's behavior changes, you can adapt your campaigns to better suit the cluster. The latest techniques blend cluster-based segmentation with deeper customer information acquired via data mining. Data mining uses algorithms to interrogate data within a database, and can produce information such as buying frequency and product types.

This new method of market segmentation, combining segmentation with data mining, provides marketers with high quality information on how their customers shop for and purchase their products or services. By combining standard market segmentation with data mining techniques you can better predict and model the behavior of your segments.



Source: http://ezinearticles.com/?New-Method-of-Market-Segmentation---Combining-Segmentation-With-Data-Mining&id=6890243

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

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

Know What the Truth Behind Data Mining Outsourcing Service

We came to that, what we call the information age where industries are like useful data needed for decision-making, the creation of products - among other essential uses for business. Information mining and converting them to useful information is a part of this trend that allows companies to reach their optimum potential. However, many companies that do not meet even one deal with data mining question because they are simply overwhelmed with other important tasks. This is where data mining outsourcing comes in.

There have been many definitions to introduced, but it can be simply explained as a process that involves sorting through large amounts of raw data to extract valuable information needed by industries and enterprises in various fields. In most cases this is done by professionals, professional organizations and financial analysts. He has seen considerable growth in the number of sectors or groups that enter my self.
There are a number of reasons why there is a rapid growth in data mining outsourcing service subscriptions. Some of them are presented below:

A wide range of services

Many companies are turning to information mining outsourcing, because they cover a wide range of services. These services include, but are not limited to data from web applications congregation database, collect contact information from different sites, extract data from websites using the software, the sort of stories from sources news, information and accumulate commercial competitors.

Many companies fall

Many industries benefit because it is fast and realistic. The information extracted by data mining service providers of outsourcing used in crucial decisions in the field of direct marketing, e-commerce, customer relationship management, health, scientific tests and other experimental work, telecommunications, financial services, and a whole lot more.

A lot of advantages

Subscribe data mining outsourcing services it's offers many benefits, as providers assures customers to render services to world standards. They strive to work with improved technologies, scalability, sophisticated infrastructure, resources, timeliness, cost, the system safer for the security of information and increased market coverage.

Outsourcing allows companies to focus their core business and can improve overall productivity. Not surprisingly, information mining outsourcing has been a first choice of many companies - to propel the business to higher profits.



Source: http://ezinearticles.com/?Know-What-the-Truth-Behind-Data-Mining-Outsourcing-Service&id=5303589

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

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

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

Who Can Benefit From Data Mining Services?

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

How is Raw Data Converted to Useful Information?

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

Our team of data mining, extraction and analyses experts have already helped a great number of businesses to tap into the potential of their raw data, with our speedy, cost-efficient and confidential services. Contact us today for more information on how our data mining and extraction services can help your business.



Source: http://ezinearticles.com/?Unleash-the-Hidden-Potential-of-Your-Business-Data-With-Data-Mining-and-Extraction-Services&id=4642076

Core Benefits of Data Entry Outsourcing Services

Due to globalization of businesses and the world becoming a united marketplace, the need for effective data entry solutions have surfaced. Data is one of the most important parts of any company. Its appropriate management is very essential in order to keep the business running smoothly and effortlessly. In order to have reliable data handling, obtaining services from a data entry company helps.

In today's market, data entry solutions for different types of businesses are available at very competitive prices. An increasing number of companies are turning to data entry outsourcing services. Hiring offshore companies for outsourcing addresses the challenge of obtaining better work quality from qualified professionals in a cost effective and timely manner.

The benefits of data entry outsourcing services include:

a) When an organization grows, it has to face many issues related to employees, their benefits, keeping pace with new technology, employees' healthcare, having the latest business information, and so on. When a company outsources some of their responsibilities, many of these issues get resolved automatically. The same holds true for data entry service.

b) India is preferred by many companies for data entry outsourcing. Various back office functions are taken care of, and the benefits of quality processes, global delivery, and better infrastructure are enjoyed, thus enabling you to give attention to other core business issues.

g) Data entry solutions firms offer numerous services such as data processing, image scanning, data formatting, file conversion, data security, SGML/HTML coding, etc. These outsourcing companies can provide data in various formats including XML, MS Word, MS Excel, JPG, DBF, and HTML.

h) Better data management and a high quality of service can be expected with timely delivery from data outsourcing companies. They hire qualified and experienced professionals, and use the latest technology in order to get more clients and stay ahead of fellow competitors.

i) Data processing is used in businesses of all sizes and is very useful for them. It is more than just the implementation of data at the right place and time. They cover all important aspects of data handling and use them for your company's profit.

j) Online data entry outsourcing services minimizes the capital cost of infrastructure and management problems. There is a greater level of employee's job satisfaction due to a reduction of mundane and uninteresting data entry tasks. These companies make the best possible use of their international resources. You can expect high output at lower costs.

Data entry outsourcing can relieve lots of time-consuming and tedious responsibilities for a company. Outsourcing to India is the ultimate answer for the challenge of cutting costs and increasing profit margins.



Source: http://ezinearticles.com/?Core-Benefits-of-Data-Entry-Outsourcing-Services&id=1548011

Internet Data Mining - How Does it Help Businesses?

Internet has become an indispensable medium for people to conduct different types of businesses and transactions too. This has given rise to the employment of different internet data mining tools and strategies so that they could better their main purpose of existence on the internet platform and also increase their customer base manifold.

Internet data-mining encompasses various processes of collecting and summarizing different data from various websites or webpage contents or make use of different login procedures so that they could identify various patterns. With the help of internet data-mining it becomes extremely easy to spot a potential competitor, pep up the customer support service on the website and make it more customers oriented.

There are different types of internet data_mining techniques which include content, usage and structure mining. Content mining focuses more on the subject matter that is present on a website which includes the video, audio, images and text. Usage mining focuses on a process where the servers report the aspects accessed by users through the server access logs. This data helps in creating an effective and an efficient website structure. Structure mining focuses on the nature of connection of the websites. This is effective in finding out the similarities between various websites.

Also known as web data_mining, with the aid of the tools and the techniques, one can predict the potential growth in a selective market regarding a specific product. Data gathering has never been so easy and one could make use of a variety of tools to gather data and that too in simpler methods. With the help of the data mining tools, screen scraping, web harvesting and web crawling have become very easy and requisite data can be put readily into a usable style and format. Gathering data from anywhere in the web has become as simple as saying 1-2-3. Internet data-mining tools therefore are effective predictors of the future trends that the business might take.



Source: http://ezinearticles.com/?Internet-Data-Mining---How-Does-it-Help-Businesses?&id=3860679

An Easy Way For Data Extraction

There are so many data scraping tools are available in internet. With these tools you can you download large amount of data without any stress. From the past decade, the internet revolution has made the entire world as an information center. You can obtain any type of information from the internet. However, if you want any particular information on one task, you need search more websites. If you are interested in download all the information from the websites, you need to copy the information and pate in your documents. It seems a little bit hectic work for everyone. With these scraping tools, you can save your time, money and it reduces manual work.

The Web data extraction tool will extract the data from the HTML pages of the different websites and compares the data. Every day, there are so many websites are hosting in internet. It is not possible to see all the websites in a single day. With these data mining tool, you are able to view all the web pages in internet. If you are using a wide range of applications, these scraping tools are very much useful to you.

The data extraction software tool is used to compare the structured data in internet. There are so many search engines in internet will help you to find a website on a particular issue. The data in different sites is appears in different styles. This scraping expert will help you to compare the date in different site and structures the data for records.

And the web crawler software tool is used to index the web pages in the internet; it will move the data from internet to your hard disk. With this work, you can browse the internet much faster when connected. And the important use of this tool is if you are trying to download the data from internet in off peak hours. It will take a lot of time to download. However, with this tool you can download any data from internet at fast rate.There is another tool for business person is called email extractor. With this toll, you can easily target the customers email addresses. You can send advertisement for your product to the targeted customers at any time. This the best tool to find the database of the customers.

However, there are some more scraping tolls are available in internet. And also some of esteemed websites are providing the information about these tools. You download these tools by paying a nominal amount.



Source: http://ezinearticles.com/?An-Easy-Way-For-Data-Extraction&id=3517104

Data Discovery vs. Data Extraction

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

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

In the data extraction phase you've already arrived at the page containing the data you're interested in, and you now need to pull it out of the HTML. Traditionally this has typically involved creating a series of regular expressions that match the pieces of the page you want (e.g., URL's and link titles). Regular expressions can be a bit complex to deal with, so most screen-scraping applications will hide these details from you, even though they may use regular expressions behind the scenes.

As an addendum, I should probably mention a third phase that is often ignored, and that is, what do you do with the data once you've extracted it? Common examples include writing the data to a CSV or XML file, or saving it to a database. In the case of a live web site you might even scrape the information and display it in the user's web browser in real-time. When shopping around for a screen-scraping tool you should make sure that it gives you the flexibility you need to work with the data once it's been extracted.



Source: http://ezinearticles.com/?Data-Discovery-vs.-Data-Extraction&id=165396

Benefits of Predictive Analytics and Data Mining Services

Predictive Analytics is the process of dealing with variety of data and apply various mathematical formulas to discover the best decision for a given situation. Predictive analytics gives your company a competitive edge and can be used to improve ROI substantially. It is the decision science that removes guesswork out of the decision-making process and applies proven scientific guidelines to find right solution in the shortest time possible.

Predictive analytics can be helpful in answering questions like:

    Who are most likely to respond to your offer?
    Who are most likely to ignore?
    Who are most likely to discontinue your service?
    How much a consumer will spend on your product?
    Which transaction is a fraud?
    Which insurance claim is a fraudulent?
    What resource should I dedicate at a given time?

Benefits of Data mining include:

    Better understanding of customer behavior propels better decision
    Profitable customers can be spotted fast and served accordingly
    Generate more business by reaching hidden markets
    Target your Marketing message more effectively
    Helps in minimizing risk and improves ROI.
    Improve profitability by detecting abnormal patterns in sales, claims, transactions etc
    Improved customer service and confidence
    Significant reduction in Direct Marketing expenses

Basic steps of Predictive Analytics are as follows:

    Spot the business problem or goal
    Explore various data sources such as transaction history, user demography, catalog details, etc)
    Extract different data patterns from the above data
    Build a sample model based on data & problem
    Classify data, find valuable factors, generate new variables
    Construct a Predictive model using sample
    Validate and Deploy this Model

Standard techniques used for it are:

    Decision Tree
    Multi-purpose Scaling
    Linear Regressions
    Logistic Regressions
    Factor Analytics
    Genetic Algorithms
    Cluster Analytics
    Product Association



Source: http://ezinearticles.com/?Benefits-of-Predictive-Analytics-and-Data-Mining-Services&id=4766989

Important Data Processing Services Can Help Your Business

Data Processing is nothing but conversion of unorganized data into useful formation. Information in itself is useless unless it is in a form where meaning could be derived out of it. Data processing consists of tasks that involve entering of data into the computer, summarize it and present it in a way that users can understand it and use the data as required.

It is very common these days to outsource data processing services. Service providers have developed many automated processes that processes information in no time which results in considerable reduction in cost and effort. More over it offers a chance to the business managers to concentrate more on core tasks of business and secondary tasks are taken care of by some expert at nominal charges.

Following are few of the important data processing services that can help business considerably:
• Forms processing: processing of forms like application forms, registration forms, admission forms etc.
• Cheque processing: like scanning, verification and evaluation, truncation and market assessment of cheques.
• Image processing: scanning, enhancing, optimizing and converting the images into desired format.
• OCR Clean up: recognition of errors and inconsistencies of a large amount of figures and elimination of same to produce a quality document.
• Survey Processing: questionnaire preparation, punching of the result of the survey, analysis and interpretation of survey feedback, designing of presentation of graphics for analysis.
• Data Mining: Accumulation of data and meta data, online data search and collection information through various websites and other online resources.
• Data Cleansing: eliminate discrepancies in data and information accuracy. It involves homogenizing, validation and rectification of records.


Source: http://ezinearticles.com/?Important-Data-Processing-Services-Can-Help-Your-Business&id=5508190

Data Entry - 5 Concerns While Outsourcing Data Entry

The world becomes open market for your business because of globalization. Business must set high efficiency level to encourage the output. Apart from core business, one has to perform non-core activities to smoothen the business performance. Managing information is one of the monotonous activities. You can go for data entry but it is, once again, mind-numbing and time-consuming task.

Companies can pick data entry firm in order to have accurate and reliable information handling. There are various data typing services available for different types of businesses for reasonable cost. However, there are continues growth of data typing firms; one must find the best practice and reputed firm to outsource.

Here are 5 concerns while outsourcing data entry:

Affordable Cost: it is the most concern issue of almost any firm that wants to outsource. It is very true that one can save up to 60% of their data typing cost if they outsource such task to country like India.

High Accuracy: The accurate output is also important factor that matters a lot while outsourcing. Without accurate information, companies can not take proper decision and make loss. A good data typing firm is offering 99.98% accuracy. So, there is no need to worry about such.

Time Frame: Companies require the information quickly. If you have huge information and want typing, choose the firm having numbers of professionals and using special techniques to quicken the task.

Data Confidentiality: After listening much about fraud and scam of data typing firm, companies are most concern about the security of data. If you will outsource the requirement to genuine and promising company, your issue of data security will get resolved.

Genuine: Is the firm genuine? Answer is simple. Get the track record of that firm as well as get input from the clients of that firm which you want to outsource.

Although there are such benefits of outsourcing data entry, organizations are staying away from outsourcing because of fraud. To avoid scam, always, ask for the trial or pilot project. So, you will get better idea about their promises and can choose better source for outsourcing data typing.


Source: http://ezinearticles.com/?Data-Entry---5-Concerns-While-Outsourcing-Data-Entry&id=4640239

Outsource Data Entry Services - A Big "CATCH" For Your Business

A thread called globalization that goes on expanding commercial boundaries between business firms in every nook and corner of this world also triggers the chords of outsourcing. A company manages to stay afloat seeing off few deadly tides and some rampant swerving on its rugged path by safely moving on few crucial lifeboats called information. Without information any business-be it a thriving one or a newly started one- meets its fate called winding-up since at crucial junctures of its business life cycle is largely dependent on information. Only when your lifeboat is out of harm your passage across any terrain remains safe. On a similar note when dedicated people deployed by authentic data entry services help in organizing unprocessed data so that it becomes valid information your business is sure to sustain making the most of the clarity of the information in hand.

Outsourcing data entry is a good plan unless you figure out the best in that business and delegate them tasks that are quite feasible to undertake with due respect to the time frame. It is always better to have some companies beside to share some volume of tasks related to information as though your business strives to manage bigger projects the quality of delivery is quite there in that high range only if your business sticks to the level it can actually manage to hold. Is it necessary for the firm to place its toes on a thing that it knows is beyond its reach? As advised by many tycoons outsourcing such services is quite essential from a business' perspective to ensure same performance without any anomaly.

In the coming paragraphs let us look into why a business is advised to eye outsourcing data entry services as a serious option?

Cost Minimization

Business firms need not invest much in developing infrastructure that is quite necessary to carry out such services within your organization. No need for a company to train candidates and place them on jobs that certainly saves a lot of money, which can be wisely invested for maximizing profits.

Adaptability

This trait comes to fullest utility when your business firm sees an opportunity to diversify its business operations by resorting to operating with a mix of products or services. A relevant or appropriate task can be delegated to outsourcing services so as to let them do their best for your services independently. For this you may even think about deploying quite a lot of dependable data entry services out there.

Technologically Advanced

Whatever be the place of outsourcing there has to be technical progression or else there is no scope in outsourcing projects to that place. Every business that deals with outsourcing services would like to keep up with technological furtherance so as to stay active in the industry.

Completeness

As many data entry services, which take up outsourcing as a primary means of flourishing in the market, render complete business services related to data entry paying heed to the needs of the company that has outsourced. By complete I like to signify that a whole lot of services categorized into an assortment are rightly offered.

Highly Effective

India rules the world when it boils down to providing excellent results in projects that are being outsourced. A perfect infrastructure coupled with adept professionals who are all motivated to push their standards further thus helping your business grow highly effective.

With all these benefits inherently available with such companies making your mind as to outsourcing data entry services is a wise option strategically.


Source: http://ezinearticles.com/?Outsource-Data-Entry-Services---A-Big-CATCH-For-Your-Business&id=4638218

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.


Source: http://ezinearticles.com/?Data-Mining---Critical-for-Businesses-to-Tap-the-Unexplored-Market&id=6745886

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.


Source: http://ezinearticles.com/?Data-Mining-vs-Screen-Scraping&id=146813