Tuesday, 30 July 2013

Data Mining Explained

Overview
Data mining is the crucial process of extracting implicit and possibly useful information from data. It uses analytical and visualization techniques to explore and present information in a format which is easily understandable by humans.

Data mining is widely used in a variety of profiling practices, such as fraud detection, marketing research, surveys and scientific discovery.

In this article I will briefly explain some of the fundamentals and its applications in the real world.

Herein I will not discuss related processes of any sorts, including Data Extraction and Data Structuring.

The Effort
Data Mining has found its application in various fields such as financial institutions, health-care & bio-informatics, business intelligence, social networks data research and many more.

Businesses use it to understand consumer behavior, analyze buying patterns of clients and expand its marketing efforts. Banks and financial institutions use it to detect credit card frauds by recognizing the patterns involved in fake transactions.

The Knack
There is definitely a knack to Data Mining, as there is with any other field of web research activities. That is why it is referred as a craft rather than a science. A craft is the skilled practicing of an occupation.

One point I would like to make here is that data mining solutions offers an analytical perspective into the performance of a company depending on the historical data but one need to consider unknown external events and deceitful activities. On the flip side it is more critical especially for Regulatory bodies to forecast such activities in advance and take necessary measures to prevent such events in future.

In Closing
There are many important niches of Web Data Research that this article has not covered. But I hope that this article will provide you a stage to drill down further into this subject, if you want to do so!

Should you have any queries, please feel free to mail me. I would be pleased to answer each of your queries in detail.


Source: http://ezinearticles.com/?Data-Mining-Explained&id=4341782

Monday, 29 July 2013

Backtesting & Data Mining

In this article we'll take a look at two related practices that are widely used by traders called Backtesting and Data Mining. These are techniques that are powerful and valuable if we use them correctly, however traders often misuse them. Therefore, we'll also explore two common pitfalls of these techniques, known as the multiple hypothesis problem and overfitting and how to overcome these pitfalls.

Backtesting

Backtesting is just the process of using historical data to test the performance of some trading strategy. Backtesting generally starts with a strategy that we would like to test, for instance buying GBP/USD when it crosses above the 20-day moving average and selling when it crosses below that average. Now we could test that strategy by watching what the market does going forward, but that would take a long time. This is why we use historical data that is already available.

"But wait, wait!" I hear you say. "Couldn't you cheat or at least be biased because you already know what happened in the past?" That's definitely a concern, so a valid backtest will be one in which we aren't familiar with the historical data. We can accomplish this by choosing random time periods or by choosing many different time periods in which to conduct the test.

Now I can hear another group of you saying, "But all that historical data just sitting there waiting to be analyzed is tempting isn't it? Maybe there are profound secrets in that data just waiting for geeks like us to discover it. Would it be so wrong for us to examine that historical data first, to analyze it and see if we can find patterns hidden within it?" This argument is also valid, but it leads us into an area fraught with danger...the world of Data Mining

Data Mining

Data Mining involves searching through data in order to locate patterns and find possible correlations between variables. In the example above involving the 20-day moving average strategy, we just came up with that particular indicator out of the blue, but suppose we had no idea what type of strategy we wanted to test? That's when data mining comes in handy. We could search through our historical data on GBP/USD to see how the price behaved after it crossed many different moving averages. We could check price movements against many other types of indicators as well and see which ones correspond to large price movements.

The subject of data mining can be controversial because as I discussed above it seems a bit like cheating or "looking ahead" in the data. Is data mining a valid scientific technique? On the one hand the scientific method says that we're supposed to make a hypothesis first and then test it against our data, but on the other hand it seems appropriate to do some "exploration" of the data first in order to suggest a hypothesis. So which is right? We can look at the steps in the Scientific Method for a clue to the source of the confusion. The process in general looks like this:

Observation (data) >>> Hypothesis >>> Prediction >>> Experiment (data)

Notice that we can deal with data during both the Observation and Experiment stages. So both views are right. We must use data in order to create a sensible hypothesis, but we also test that hypothesis using data. The trick is simply to make sure that the two sets of data are not the same! We must never test our hypothesis using the same set of data that we used to suggest our hypothesis. In other words, if you use data mining in order to come up with strategy ideas, make sure you use a different set of data to backtest those ideas.

Now we'll turn our attention to the main pitfalls of using data mining and backtesting incorrectly. The general problem is known as "over-optimization" and I prefer to break that problem down into two distinct types. These are the multiple hypothesis problem and overfitting. In a sense they are opposite ways of making the same error. The multiple hypothesis problem involves choosing many simple hypotheses while overfitting involves the creation of one very complex hypothesis.

The Multiple Hypothesis Problem

To see how this problem arises, let's go back to our example where we backtested the 20-day moving average strategy. Let's suppose that we backtest the strategy against ten years of historical market data and lo and behold guess what? The results are not very encouraging. However, being rough and tumble traders as we are, we decide not to give up so easily. What about a ten day moving average? That might work out a little better, so let's backtest it! We run another backtest and we find that the results still aren't stellar, but they're a bit better than the 20-day results. We decide to explore a little and run similar tests with 5-day and 30-day moving averages. Finally it occurs to us that we could actually just test every single moving average up to some point and see how they all perform. So we test the 2-day, 3-day, 4-day, and so on, all the way up to the 50-day moving average.

Now certainly some of these averages will perform poorly and others will perform fairly well, but there will have to be one of them which is the absolute best. For instance we may find that the 32-day moving average turned out to be the best performer during this particular ten year period. Does this mean that there is something special about the 32-day average and that we should be confident that it will perform well in the future? Unfortunately many traders assume this to be the case, and they just stop their analysis at this point, thinking that they've discovered something profound. They have fallen into the "Multiple Hypothesis Problem" pitfall.

The problem is that there is nothing at all unusual or significant about the fact that some average turned out to be the best. After all, we tested almost fifty of them against the same data, so we'd expect to find a few good performers, just by chance. It doesn't mean there's anything special about the particular moving average that "won" in this case. The problem arises because we tested multiple hypotheses until we found one that worked, instead of choosing a single hypothesis and testing it.

Here's a good classic analogy. We could come up with a single hypothesis such as "Scott is great at flipping heads on a coin." From that, we could create a prediction that says, "If the hypothesis is true, Scott will be able to flip 10 heads in a row." Then we can perform a simple experiment to test that hypothesis. If I can flip 10 heads in a row it actually doesn't prove the hypothesis. However if I can't accomplish this feat it definitely disproves the hypothesis. As we do repeated experiments which fail to disprove the hypothesis, then our confidence in its truth grows.

That's the right way to do it. However, what if we had come up with 1,000 hypotheses instead of just the one about me being a good coin flipper? We could make the same hypothesis about 1,000 different people...me, Ed, Cindy, Bill, Sam, etc. Ok, now let's test our multiple hypotheses. We ask all 1000 people to flip a coin. There will probably be about 500 who flip heads. Everyone else can go home. Now we ask those 500 people to flip again, and this time about 250 will flip heads. On the third flip about 125 people flip heads, on the fourth about 63 people are left, and on the fifth flip there are about 32. These 32 people are all pretty amazing aren't they? They've all flipped five heads in a row! If we flip five more times and eliminate half the people each time on average, we will end up with 16, then 8, then 4, then 2 and finally one person left who has flipped ten heads in a row. It's Bill! Bill is a "fantabulous" flipper of coins! Or is he?

Well we really don't know, and that's the point. Bill may have won our contest out of pure chance, or he may very well be the best flipper of heads this side of the Andromeda galaxy. By the same token, we don't know if the 32-day moving average from our example above just performed well in our test by pure chance, or if there is really something special about it. But all we've done so far is to find a hypothesis, namely that the 32-day moving average strategy is profitable (or that Bill is a great coin flipper). We haven't actually tested that hypothesis yet.

So now that we understand that we haven't really discovered anything significant yet about the 32-day moving average or about Bill's ability to flip coins, the natural question to ask is what should we do next? As I mentioned above, many traders never realize that there is a next step required at all. Well, in the case of Bill you'd probably ask, "Aha, but can he flip ten heads in a row again?" In the case of the 32-day moving average, we'd want to test it again, but certainly not against the same data sample that we used to choose that hypothesis. We would choose another ten-year period and see if the strategy worked just as well. We could continue to do this experiment as many times as we wanted until our supply of new ten-year periods ran out. We refer to this as "out of sample testing", and it's the way to avoid this pitfall. There are various methods of such testing, one of which is "cross validation", but we won't get into that much detail here.


Source: http://ezinearticles.com/?Backtesting-and-Data-Mining&id=341468

Sunday, 28 July 2013

What Are the Pros and Cons of Outsourcing Data Entry Services?

A number of business firms now outsource their non-core back office tasks to external companies to save their money, time and effort. However, before assigning your data processing and data entry jobs to third party providers, it is good to consider the major pros and cons of outsourcing data entry services. With a clear insight as regards the advantages and disadvantages of outsourcing, you can decide whether outsourcing is a right option for your business organization.

Professional Data Entry Services Offer an Assortment of Benefits

The important advantage of outsourcing these services is that it helps to streamline your business functions. When you assign your data entry jobs to professional BPO companies you can get the work done promptly in a short span of time. These services ensure an assortment of additional benefits such as:

• Saves your money: Outsourcing these services enables you to save on the money that would be required to appoint additional staff, and maintain the infrastructure essential to carry out the data processing tasks within your organization. You can avoid any additional outlay involved in terms of providing salaries, compensations, incentives and other allowances for your data processing staff.

• Business records in organized formats: Business process outsourcing services from reliable firms allow you to keep business records without any errors in properly organized formats.

• Reduce your workload: Well-planned services significantly reduce your managerial responsibilities, and save you the time and effort required to complete the monotonous and time consuming data processing jobs. These services enable you to concentrate on core competencies with improved efficiency.

• Enhance business productivity and cash flow: Outsourcing data entry services would help you enhance the efficiency and productivity of your corporate firm, which would in turn increase your sales leads and cash flow.

• Deliver better customer support: When you outsource the data processing jobs, you get more time to plan and deliver the best services for your customers, which would ensure better business benefits.

• Share your business risks: Business process outsourcing services provide you an opportunity to share your business risks with an external agency.

In other words, outsourcing data entry services help business entities to remain competitive in the business scenario through modernizing their core processes. Realizing these many benefits, many organizations are now assigning their data processing jobs to external companies.

Cons of Data Entry Outsourcing

• Lack of focus: At times, most BPO service providers might offer data entry services that do not match exactly with your specific requirements. This might affect your business operations.

• Accessibility to confidential data: When you outsource your core data entry jobs such as accounting, payroll processing, HR and recruitment, insurance claim processing and other tasks, the BPO companies would get a chance to access the more personal and confidential information of your organization.

• Inconsistency in output quality: If the provider you have chosen is inexperienced and lacks consistency, then it might lead to problems such as delayed submission of completed projects, processed files without accuracy and quality, inappropriate assignment of responsibilities, lack of communication and so on.

Partner with an Experienced BPO Company

Briefly, the pros absolutely override the cons of outsourcing data entry services. However, to get the best of merits from these services, ensure that you associate with an experienced company. Established business process outsourcing companies can deliver precise data processing solutions that best suit your requirements and budget limits, in rapid turnaround time.



Source: http://ezinearticles.com/?What-Are-the-Pros-and-Cons-of-Outsourcing-Data-Entry-Services?&id=6271210

Friday, 26 July 2013

Data Entry Services Are The Core of Any Business

Data entry is the core of any business and though it may appear to be easy to manage and handle, this involves many processes that need to be dealt systematically. Huge changes have taken place in the field of data entry and due to this handling the work has become much easier then before. So if you want to make use of the best data entry services to maintain the data and other information about your company, you must be ready to spend money for this. It is in no way an attempt to say that data entry services are costly, but just to say that good services will not come that cheap either. You just need to decide if you will hire professionals to do this work in house or if you would like to hire the services from an outside firm. The business is your and you are the best person to decide what is suitable for your business.

Doing the data entry of any business in house can be advantageous and disadvantageous as well. The main advantage can be in the form that you can keep an eye on the work being done to maintain proper records of all aspects of your company. This can prove to be a bit costly to you as you will have to hire the services of a data entry operator. The employee will be on rolls and thus will be entitled to all the benefits like allowances and other bonuses. So another option that you can use for this is to get a third party handle the work for you. This is a better option as you can hire the services depending on the type of work you need to be done.

This is one of the core components of your business and consequently you must ensure that this is handled properly. Data entry services are not the only aspect that business owners are seeking out these days. With the huge surge in the field of information and technology data conversion is equally important. The need to convert the data that has been entered is gaining momentum day by day. Conversion of the data makes it more accessible and this can be used easily without too many hassles to draw customers for buying the goods. Traditional methods have been done away with and professionals who work for data entry services these days are highly skilled and in tune with the latest methods.

Data entry services done for a company by third party has been found to be very suitable. In fact studies have indicated that outsourcing data entry services is one the rise due to the high rate of success enjoyed by business owners for this. The main advantage of getting data entry services done by a third party is that it works out very cheap and the work done is of the top most quality. So if the data entry services of the best quality id provided there is absolutely no chance why someone would not undertake the process to increase and brighten business prospects.



Source: http://ezinearticles.com/?Data-Entry-Services-Are-The-Core-of-Any-Business&id=556117

Thursday, 25 July 2013

Data Entry Outsourcing - 6 Key Benefits of Outsourced Data Entry

The effective data typing services are must and have to outsource because of globalization. Without information, no company can go ahead and become successful. At every point of making decisions, proper information is essential. So data is one of the most important parts in any organization. There must be proper management to keep the business running smoothly and effectively.

If you want reliable source for data handling, hire typing service company to outsource data entry task. Currently, solutions for every type of business needs are available at reasonable rate. As business grow, it is very hard to manage huge information. So, companies are turning to data entry outsourcing.

Here are the key benefits of data entry outsourcing:

1. All-in-One: data entry firms are offering numbers of services like, data processing, scanning, information formatting, document conversion, indexing and others. They also understand your requirement and deliver the output required format such as Word, Excel, JPG, HTML, XML and Other.

2. Resolve the Issues: As company grows, there are many issues arise like information about employees, benefits, healthcare for them, tuning with rapidly changing technologies, latest business information and others. If organization outsources some of their responsibilities, various issues get resolved quickly and automatically.

3. Better Services: You can expect superior data management and high quality services from outsourcing companies. They have experienced and skilled professionals with latest technologies to deliver unexpected result and stay ahead of other.

4. Least Cost: You can lower down your capital cost of infrastructure and other cost of salary, stationery and other, if you outsource data typing task. Through offshore companies, you can easily save up to 60% on data typing services.

5. Higher Efficiency: If your employees are free from routine and uninteresting process of entering information, they can deliver better result. Ultimately, this can increase the job satisfaction level and efficiency. You can expect high output at lower costs.

6. Place of Outsourcing: You must think about the outsourcing country. India is chosen by various companies for data typing outsourcing. At India, you can get benefits of better quality, enough infrastructure, quick delivery, skilled experts at very low rates.

You can easily reduce tons of time-consuming and boring responsibilities by outsourcing.


Source: http://ezinearticles.com/?Data-Entry-Outsourcing---6-Key-Benefits-of-Outsourced-Data-Entry&id=4253927

Sunday, 21 July 2013

Business Intelligence Data Mining

Data mining can be technically defined as the automated extraction of hidden information from large databases for 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.

Data mining requires the use of mathematical algorithms and statistical techniques integrated with software tools. The final product is an easy-to-use software package that can be used even by non-mathematicians to effectively analyze the data they have. Data Mining is used in several applications like market research, consumer behavior, direct marketing, bioinformatics, genetics, text analysis, fraud detection, web site personalization, e-commerce, healthcare, customer relationship management, financial services and telecommunications.

Business intelligence data mining 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, healthcare, the oil and gas industry, scientific tests, genetics, telecommunications, financial services and utilities. BI uses various technologies like data mining, scorecarding, data warehouses, text mining, decision support systems, executive information systems, management information systems and geographic information systems for analyzing useful information for business decision making.

Business intelligence is a broader arena of decision-making that uses data mining as one of the tools. In fact, the use of data mining in BI makes the data more relevant in application. There are several kinds of data mining: text mining, web mining, social networks data mining, relational databases, pictorial data mining, audio data mining and video data mining, that are all used in business intelligence applications.

Some data mining tools used in BI are: decision trees, information gain, probability, probability density functions, Gaussians, maximum likelihood estimation, Gaussian Baves classification, cross-validation, neural networks, instance-based learning /case-based/ memory-based/non-parametric, regression algorithms, Bayesian networks, Gaussian mixture models, K-means and hierarchical clustering, Markov models and so on.


Source: http://ezinearticles.com/?Business-Intelligence-Data-Mining&id=196648

Friday, 19 July 2013

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

Wednesday, 17 July 2013

Data Mining Process - Why Outsource Data Mining Service?

Overview of Data Mining and Process:
Data mining is one of the unique techniques for investigating information to extract certain data patterns and decide to outcome of existing requirements. Data mining is widely use in client research, services analysis, market research and so on. It is totally based on mathematical algorithm and analytical skills to drive the desired results from the huge database collection.

Information mining is mostly used by financial analyzer, business and professional organization and also there are many growing area of business that are get maximum advantages of data extract with use of data warehouses in their small to large level of businesses.

Most of functionalities which are used in information collecting process define as under:

* Retrieving Data

* Analyzing Data

* Extracting Data

* Transforming Data

* Loading Data

* Managing Databases

Most of small, medium and large levels of businesses are collect huge amount of data or information for analysis and research to develop business. Such kind of large amount will help and makes it much important whenever information or data required.

Why Outsource Data Online Mining Service?

Outsourcing advantages of data mining services:
o Almost save 60% operating cost
o High quality analysis processes ensuring accuracy levels of almost 99.98%
o Guaranteed risk free outsourcing experience ensured by inflexible information security policies and practices
o Get your project done within a quick turnaround time
o You can measure highly skilled and expertise by taking benefits of Free Trial Program.
o Get the gathered information presented in a simple and easy to access format

Thus, data or information mining is very important part of the web research services and it is most useful process. By outsource data extraction and mining service; you can concentrate on your co relative business and growing fast as you desire.

Outsourcing web research is trusted and well known Internet Market research organization having years of experience in BPO (business process outsourcing) field.

If you want to more information about data mining services and related web research services, then contact us.


Source: http://ezinearticles.com/?Data-Mining-Process---Why-Outsource-Data-Mining-Service?&id=3789102

Thursday, 11 July 2013

Data Extraction Software Explained in Plain English

Data Extraction Software is designed to automatically collect data from web pages. A lot of money can be made with Data Extraction Software, but there are two types of program - custom made and typical.

Custom made solutions are designed by developers to extract from one particular source and they can't automatically adjust to another. So for example, if we are to create a custom-build data extraction program for website A, it won't work for website B, because they have different structures. Such custom made solutions cost more money than the standard ones, but they are designed for more complicated and unique situations.

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

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

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

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


Source: http://ezinearticles.com/?Data-Extraction-Software-Explained-in-Plain-English&id=1477227

Wednesday, 10 July 2013

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.


Source: http://ezinearticles.com/?Importance-of-Data-Mining-Services-in-Business&id=2601221

Monday, 8 July 2013

About Outsourcing Data Entry Services

Data can be defined as numbers or characters that usually represent the dimensions or measurements. Data entry can be applied to any process that coverts data from one form to another. These services cover almost all business and professional services like data conversion, online and offline data entry, document and image processing; image entry, insurance claim entry, data processing, form processing, etc. Also collecting numerous data related to certain topics and then to present them in meaningful & easy to understand presentations.

Data entry services are very useful in business firms and organizations as there is a huge demand of entry work. These services are considered as the central part in any of the businesses. These services are useful to organize and manage your data/information in digital format. One of the types is data processing that generally programmed on a mainframe, minicomputer, microcomputer or personal computer. These systems are used for entry related work and to convert data into information.

About Data Entry Outsourcing
Outsourcing means to hire the services from a third party for your requirements. No sooner did outsourcing get support from the global technological development than business organizations started outsourcing entry. Data entry outsourcing is a simple contract between two different identities for any type of data entry service.

The main purpose for doing outsourcing is the availability of qualified and experienced computer operators at low cost. There are various types of entry operations such as data conversion, data processing, catalog processing services, image enhancement, image editing and photo manipulation services, etc, provided by BPO Services firms.

How helpful Services are?
o Data entry services help the companies for sharpening their foundation, analyzing their operations, strategies, policies, activities.

o Data processing services also encircle a variety of methods for how data is processed and to what extent the data is prepared to yield the best of the outcomes for the company.

o Data Conversion services help the business to convert information into easy format that is useful to increase online and offline popularity of business.

These all mechanisms help large as well as small business to enhance their internal process. These also help companies to increase their productivity and develop healthy external contacts.


Source: http://ezinearticles.com/?About-Outsourcing-Data-Entry-Services&id=2747714

Saturday, 6 July 2013

How Data Mining is Useful to Companies?

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

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

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

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

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

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

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


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

Friday, 5 July 2013

Data Mining and Its Impact on Business

Today, businesses are collecting more information that is available in a variety of formats. This includes: operational data, sales reports, customer data, inventory lists, forecast data, etc. In order to effectively manage and grow the business, all of the data gathered requires effective management and analysis. One such way of controlling the vast amount of information flow is a process called Data Mining.

Data mining is the process of taking a large amount of data and analyzing it from a variety of angles and putting into a format that makes it useful information to help a business improve operations, reduce costs, boost revenue, and make better business decisions. Today, effective data mining software has developed to help a business to collect and analyze useful information.

This process allows a business to collect data from a variety of sources, analyze the data using software, load the information into a database, store the information, and provide analyzed data in a useful format such as a report, table, or graph. As it relates to business analysis and business forecasting, the information analyzed is classified to determine important patterns and relationships. The idea is to identify relationships, patterns, and correlations from a broad number of different angles from a large database. These kinds of software and techniques allow a business easy access to a much simpler process which makes it more lucrative.

Data mining works allows a company to use the information to maintain competitiveness in a highly competitive business world. For instance, a company may be collecting a large volume of information from various regions of the country such as a consumer national survey. The software can compile the mined data, categorize it, and analyze it, to reveal a host of useful information that a marketer can use for marketing strategies. The outcome of the process should be an effective business analysis that allows a company to fully understand the information in order to make accurate business decisions that contributes to the success of the business. An example of a very effective use of data mining is acquiring a large amount of grocery store scanner data and analyzing it for market research. Data mining software allows for statistical analysis, data processing, and categorization, which all helps achieve accurate results.

It is mostly used by businesses with a strong emphasis on consumer information such shopping habits, financial analysis, marketing assessments...etc. It allows a business to determine key factors such as demographics, product positioning, competition, pricing, customer satisfaction, sales, and business expenditures. The result is the business is able to streamline its operations, develop effective marketing plans, and generate more sales. The overall impact is an increase in revenue and increased profitability.

For retailers, this process allows them to use of sales transactions to develop targeted marketing campaigns based on their customers shopping habits. Today, mining applications and software are available on all system sizes and platforms. For instance, the more information that has to be gathered and processed, the bigger the database. As well, the type of software a business will use depends on how complicated the data mining project. The more multifaceted the queries and the more queries performed, the more powerful system will be needed.

When a business harnesses the power of this system, they are able to gain important knowledge that will help them not only develop effective marketing strategies leading to better business decisions, but it will help identify future trends in their particular industry. Data mining has become an essential tool to help businesses gain a competitive edge.



Source: http://ezinearticles.com/?Data-Mining-and-Its-Impact-on-Business&id=4528755

Wednesday, 3 July 2013

Outsourcing Data Entry - A Right Move

Competition that is what it is all about. Every business on the planet has a competitor and the writing on the wall is simple, stay a step ahead, which is easier said than done. Customer is the key to all business and keeping the customer happy means repeat business and proper growth. That would require companies to do research, plan marketing strategies, and always have quick access to data to process customer request. This article is not to talk about what is data entry? Or what is data processing? Rather it is to give you enough reasons to find an outsourcing partner who would get the job done for you.

Why Consider Outsourcing

Ever felt overwhelmed with work, too many things to take care of and you have a lot of catching up to do? Well that's where the idea of outsourcing comes in. Finding an outsourcing partner who could share that load and give you what you need, the way you need it and to the time that you set, is something worth looking into. Outsourcing eases your financial load; you could get the job done at a lesser cost externally than in-house. This would mean less pressure on the financial side of things.

Ever wondered how much of your time is consumed in areas that do not require it, when it could be well spent on some core parts of the process. Outsourcing your work will help take care of that. You could give your full to parts of your business that requires attention, confidently knowing that work is still getting completed half way around the globe by people who are knowledgeable about your business and understands your business process.

The workforce is always a concern. Finding the right person for the job is a task in itself and is also expensive. So without the right person on the job, you could be getting less quality and slower turn-around-time than what you bargained for. Business is money and low quality and slow work is only going to let you end up losing it than making any. With an outsourcing partner in place, the workforce, the quality, the infrastructure is a non-issue. The work is done faster at half the cost.

Now every business has some sort of risks involved and outsourcing is no different. Outsourcing would mean the transfer of key information of process and compromising on what needs to be kept hush. Also, you might not have complete control of the business activity. Fortunately, there are ways to arrest these sorts of risks. As far as keeping things under wraps is concerned one could sign in an agreement that would bind both parties in keeping information from leaking out. Making sure that your outsourcing partner is as transparent as glass to you when it comes to the people and budget should cover the problem of having control.

When choosing your outsourcing partner choose one with an accomplished track record. Investigate if the company you choose to partner with has some good accounts to show. Feedback for those accounts should help you decide if you are making a good investment or not.


Source: http://ezinearticles.com/?Outsourcing-Data-Entry---A-Right-Move&id=5221839

Monday, 1 July 2013

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