What is Data Mining?

Data mining is the process in which there is analysis of data forming different angles and perspectives and summarizing the same data into the relevant information. This kind of information could be utilized to increase the revenue, cutting the costs or both.

Software is mainly used for analyzing data and also assists in accumulation of data for the different sources and categorize and summarize the given data into some useful form.

Though the data mining is new term, the software used for mining the data was previously used. With the constant upgradations of the software and the processing power, the market tools, data mining software has increased in its accuracy. Formerly, this data mining was widely used by the businessmen for the market research and the analysis. There were few companies that used the computers to examine through the column of the supermarket data.

The data mining is the technique of running the data through the sophisticated algorithms for discovering the meaningful correlations and patterns that would have otherwise remained hidden. It is very helpful, since it aids in understanding the techniques and methods of business and you can accordingly apply your own intelligence fitting in the current market trend. Even the future performances get enhanced by the predictive analysis.

Business Intelligence operations occur in the background. Users of the mining operation can just see the end result. The users are in apposition to get the results through the mails and can also go through the recommendation through web pages and emails.

The data mining process indicates the invention of trends and tactics. The moment you discover and understand the market trends, you have the knowledge of which article is sold more and which article is sold with the other one. This kind of tend has an enormous impact on business organization. In this manner, the business gets enhanced as the market gets analyzed in a perfect manner. Due to these correlations, the performance of business organization increases to a lot of extent.

Mining gives a chance or opportunity to enhance the future performance of the business organization. There is a common philosophical phrase that, 'he who does not learn from the history is destined to repeat the same'. Therefore, if these predictions are done with the help and assistance of the historical information (data), then you can get sufficient data for improvising the products of the business organization.

Mining enables the embedding of the recommendations in the applications. Simple summary statements and the proposals can be displayed within the operational applications. Data mining also needs powerful machines. The algorithms might be applied to a Java or a Dataset code for using the same. Data mining is very useful for knowing the trends and making future predictions based on the predictive analysis. It also helps in cost cutting and increase in the revenue of the business organization


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Data Mining - Critical for Businesses to Tap the Unexplored Market

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

What Data Mining is and what it is not?

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

The 'First-mover Advantage'

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

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

The data mining algorithms and challenges

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

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

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


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Outsourcing Data Entry Services

Data or raw information is the backbone of any industry or business organization. However, raw data is seldom useful in its pure form. For it to be of any use, data has to be recorded properly and organized in a particular manner. Only then can data be processed. That is why it is important to ensure accurate data entry. But because of the unwieldy nature of data, feeding data is a repetitive and cumbersome job and it requires heavy investment, both in terms of time and energy from staff. At the same time, it does not require a high level of technical expertise. Due to these factors, data entry can safely be outsourced, enabling companies to devote their time and energy on tasks that enhance their core competence.

Many companies, big and small, are therefore enhancing their productivity by outsourcing the endless monotonous tasks that tend to cut down the organization's productivity. In times to come, outsourcing these services will become the norm and the volume of work that is outsourced will multiply. The main reason for these kinds of development is the Internet. Web based customer service and instant client support has made it possible for service providers to act as one stop business process outsourcing partners to parent companies that require support.

Data entry services are not all alike. Different clients have different demands. While some clients may require recording information coupled with document management and research, others may require additional services like form processing or litigation support. Data entry itself could be from various sources. For instances, sometimes information may need to be typed out from existing documents while at other times, data needs to be extracted from images or scanned documents. To rise up to these challenges, service providers who offer these services must have the expertise and the software to ensure rapid and accurate data entry. That is why it is important to choose your service provider with a lot of care.

Before hiring your outsourcing partner, you need to ask yourself the following questions.

* What kind of reputation does the company enjoy? Do they have sufficient years of experience? What kind of history and background does the company enjoy?

* Do they have a local management arm that you can liaise with on a regular basis?

* Do the service personnel understand your requirements and can they handle them effectively?

* What are the steps taken by the company to ensure that there is absolutely no compromise in confidentiality and security while dealing with vital confidential data?

* Is there a guarantee in place?

* What about client references?

The answers to these questions will help you identify the right partner for outsourcing your data entry service requirements.



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Beneficial Data Collection Services

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

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

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

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


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Various Data Mining Techniques

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

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

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

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

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

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

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



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Data Entry - Outsourcing the Answer to Data Entry Solution Needs

Data entry is the process of systematic and accurate copying of information by keying and scanning text, images and numerical documents into a client preferred format and data base. It is not a primary business activity and function. However smooth, efficient and competent data entry solution is required to stay competitive and to ensure customer satisfaction because businesses accumulate huge volume of information in their day to day operation.

Contrary to common views data entry is not a simple and effortless task. It involves many activities which ranges from simple to complex and to name a few we have image scanning for electronic filing, book entry, making product catalogs, indexing, claims and invoice forms entry, company reports entry, medical transcription, research and data mining, document reformatting, proof reading and updating documents related to customer information. It is a tedious job that is not only time consuming to accomplish but also requires skills and competence.

To save overhead costs companies have farmed out or outsourced noncore jobs such as data entry to countries like Philippines and India. These countries are known for their rich and inexpensive intellectual capital. Outsourcing is much more cost effective than hiring full-time employees because companies will not be paying for medical insurances, vacation leave, bonuses and other fringe benefits on top of competitive salaries. There are also other advantages in outsourcing. It also helps companies focus in their core business activities, there will be a quick turnaround time for projects and high quality of work is assured, it reduces management problems and companies can take advantage of competitive labor resources worldwide.

The National Data Entry has qualified members who can provide services to help you in data management care needs. Its membership is very diverse. They have members coming from all parts of the world from the U.S to Southeast Asia. You may enlist your company in this membership site as a job provider and for more information just browse their website in the internet. You do not have to search far and wide to get skilled, efficient but inexpensive service providers.


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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.



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The Need for Specialised Data Mining Techniques for Web 2.0

Web 2.0 is not exactly a new version of the Web, but rather a way to describe a new generation of interactive websites centred on the user. These are websites that offer

interactive information sharing, as well as collaboration - a case in point being wikis and blogs - and is now expanding to other areas as well. These new sites are the result of new technologies and new ideas and are on the cutting edge of Web development. Due to their novelty, they create a rather interesting challenge for data mining.

Data mining is simply a process of finding patterns in masses of data. There is such a vast plethora of information out there on the Web that it is necessary to use data mining tools to make sense of it. Traditional data mining techniques are not very effective when used on these new Web 2.0 sites because the user interface is so varied. Since Web 2.0 sites are created largely by user-supplied content, there is even more data to mine for valuable information. Having said that, the additional freedom in the format ensures that it is much more difficult to sift through the content to find what is usable.The data available is very valuable, so where there is a new platform, there must be new techniques developed for mining the data. The trick is that the data mining methods must themselves be flexible as the sites they are targeting are flexible. In the initial days of the World Wide Web, which was referred to as Web 1.0, data mining programs knew where to look for the desired information. Web 2.0 sites lack structure, meaning there is no single spot for the mining program to target. It must be able to scan and sift through all of the user-generated content to find what is needed. The upside is that there is a lot more data out there, which means more and more accurate results if the data can be properly utilized. The downside is that with all that data, if the selection criteria are not specific enough, the results will be meaningless. Too much of a good thing is definitely a bad thing. Wikis and blogs have been around long enough now that enough research has been carried out to understand them better. This research can now be used, in turn, to devise the best possible data mining methods. New algorithms are being developed that will allow data mining applications to analyse this data and return useful. Another problem is that there are many cul-de-sacs on the internet now, where groups of people share information freely, but only behind walls/barriers that keep it away from the genera results.

The main challenge in developing these algorithms does not lie with finding the data, because there is too much of it. The challenge is filtering out irrelevant data to get to the meaningful one. At this point none of the techniques are perfected. This makes Web 2.0 data mining an exciting and frustrating field, and yet another challenge in the never ending series of technological hurdles that have stemmed from the internet. There are numerous problems to overcome. One is the inability to rely on keywords, which used to be the best method to search. This does not allow for an understanding of context or sentiment associated with the keywords which can drastically vary the meaning of the keyword population. Social networking sites are a good example of this, where you can share information with everyone you know, but it is more difficult for that information to proliferate outside of those circles. This is good in terms of protecting privacy, but it does not add to the collective knowledge base and it can lead to a skewed understanding of public sentiment based on what social structures you have entry into. Attempts to use artificial intelligence have been less than successful because it is not adequately focused in its methodology. Data mining depends on the collection of data and sorting the results to create reports on the individual metrics that are the focus of interest. The size of the data sets are simply too large for traditional computational techniques to be able to tackle them. That is why a new answer needs to be found. Data mining is an important necessity for managing the backhaul of the internet. As Web 2.0 grows exponentially, it is increasingly hard to keep track of everything that is out there and summarize and synthesize it in a useful way. Data mining is necessary for companies to be able to really understand what customers like and want so that they can create products to meet these needs. In the increasingly aggressive global market, companies also need the reports resulting from data mining to remain competitive. If they are unable to keep track of the market and stay abreast of popular trends, they will not survive. The solution has to come from open source with options to scale databases depending on needs. There are companies that are now working on these ideas and are sharing the results with others to further improve them. So, just as open source and collective information sharing of Web 2.0 created these new data mining challenges, it will be the collective effort that solves the problems as well.

It is important to view this as a process of constant improvement, not one where an answer will be absolute for all time. Since its advent, the internet has changed quite significantly as well as the way users interact with it. Data mining will always be a critical part of corporate internet usage and its methods will continue to evolve just as the Web and its content does.

There is a huge incentive for creating better data mining solutions to tackle the complexities of Web 2.0. For this reason, several companies exist just for the purpose of analysing and creating solutions to the data mining problem. They find eager buyers for their applications in companies which are desperate for information on markets and potential customers. The companies in question do not simply want more data, they want better data. This requires a system that can classify and group data, and then make sense of the results.While the data mining process is expensive to start with, it is well worth for a retail company because it provides insight into the market and thus enables quick decisions.The speed at which a company which has insightful information on the marketplace can react to changes, gives it a huge advantage over the competition. Not only can the company react quickly, it is likely to steer itself in the right direction if its information is based on updated data.Advanced data mining will allow companies not only to make snap decisions, but also to plan long range strategies, based on the direction the marketplace is heading. Data mining brings the company closer to its customers. The real winners here, are the companies that have now discovered that they can make a living by improving the existing data mining techniques. They have filled a niche that was only created recently, which no one could have foreseen and have done quite a, good job at it.


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Website Data Scraping Are Relatively Easy To Use

Have you ever heard "data scraping?" Scraping data scraping technology to new technology and a successful entrepreneur made his fortune by taking advantage of the data is not.

Sometimes the owner of the website automatically harvest your data will not be much fun. Webmaster tools or techniques contained in the website retrieving block certain IP addresses from using their websites to disallow web scrapers learned to use. The all eventually left may be blocked.

Venus is a modern solution to the problem. Proxy data scraping technology solves this problem by using proxy IP addresses. Each time you scraping the data the program execute an exit from a website, website think it is coming from a different IP address. The owner of the website, the proxy data scraping a short period of increased traffic from all over the world look like.

Now you might ask yourself, "do I get for my project in which the data scraping technology Proxy?" "Do it yourself" solution, but unfortunately, not all madly. Hindi to mention. The proxy server you choose to rent consider hosting provider, but somewhat pricey option, but certainly better than the alternative would be incredibly dangerous (but) free public proxy server.

There are literally thousands of free proxy servers located all over the world that are relatively simple to use. But finding it misleading. Many sites list hundreds of servers, but that's hard to find, open, and support the type of protocol you need patience, trial and error, can be a lesson. But if you're working behind the scenes to the public in finding a pool is not successful, there is still the inherent risk of using it.
First, you do not know which server belongs to or what the task of going to a server in one place. Through a public proxy requests or to transmit sensitive data is a bad idea.

Proxy data scraping for a less risky situation is to rent a rotating proxy connection to cycle through a large number of private IP addresses. Company as large anonymous proxy solutions, but often carry a pretty hefty setup fee to get going.

After performing a simple Google search, I quickly that the purposes scraping anonymous company that provide access to data in the proxy server.
The proxy server you choose to rent consider hosting provider, but somewhat pricey option, but certainly better than the alternative would be incredibly dangerous (but) free public proxy server.

Some challenges will be to:

Block IP address: If you continue to keep your office scraping a website, your IP "security guard" From day one is blocked.

Unless you are an expert in programming, you will not be able to receive data.

In today's society of natural resources, its users a service that is still delivering fresh data it is moving.


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GPS Navigation Systems and Data Problems

We have a serious problem brewing with GPS navigation systems for automobiles and even motorcycles. There are however problems with this devise as a high tech toy are more serious than you might think. Ask anyone in a metro area who has bought a new car with one of those cool GPS upgrades for their SUV or new sports car. We have had our customers complain (customers of the carwash business, which is my profession). Oh they love the gadget, but they are under whelmed by the lack of data and streets, which are not listed. You see we have been seeing incredible suburban growth in many cities. Places near large DMA metros are a problem out in the middle class suburbs. In many areas such as outside Chicago, Los Angeles, San Diego, Phoenix, Las Vegas, Seattle, Portland, Denver, Dallas, Houston, Austin, San Antonio, Nashville, Kansas City, Minneapolis, Columbus, Cleveland, Baltimore, Jacksonville, Tampa Bay, Miami, Orlando, Atlanta, DC Subs, etc. And in NJ, NC, NV, OH lots of other fast growing growth pockets.

When GPS devises for cars first hit the scenes at the CES and SEMA shows in 1996, they became increasingly more popular, powerful and better data. But like VHS and Beta, Apple and IBM, competition became increasingly greater causing much consolidation in the industry along with patent fights. Much of the technology was former Defense Contractors peddling their wares through subsidiary consumer level companies. But the tight market remained due to the costs. Meanwhile companies like DeLorme and others tried to flood the market with low priced GPS units, which made things even more competitive. And the bugs were not fully out of the system yet. Someday all cars will drive themselves and people can watch TV, do video conferencing and use their transportation as a portable office or entertainment system while they are being driven to the location they have punched into their computer. Some things will have to occur before this is a reality of course. But eventually your dexterity skills to actually pilot a car will be worthless and un-needed.

First the satellites will need to be laser aligned and use multiple satellites to get absolute locations of ground items and vehicles. The cars will need to have additional anti collision devises made up of networked sonar and optic flow sensors. All of which are now available and the technology is getting better and better. Many military applications today will be civilian tomorrow. Just like Radar, Microwave ovens, Nuclear Energy, Cellular Phones, Satellite Communication and Jet Aircraft in Commercial Aviation. The flow of transportation will be brought to the next generation to serve man better.

For the time being the incremental changes in these technologies has hit a slight road block even though Honda, GM, Ford, Mercedes, Daimler Chrysler and Toyota have invested billions in anti-collision and safety devices which they will add comfort and desirable options which they can sell to customers as upgrades. Smart Car Technologies can add Thousands of Dollars to the price of a car and consumers are glad to pay for them. A factory GPS system with display can cost up to $6,000.00 and they sell a lot of them on the higher end cars. It is a high profit item upgrade, although there are some, which only cost $1000. And if you wish to compare these, some are very incredible with many features;

[http://www.gpsnuts.com/myGPS/GPS/review%20...he%20review.htm] .

There are many companies, which sell after market computer assist items. These companies are doing quite well and the systems work great. The big issue is just because you have a super duper incredible GPS system, does not mean the street you are looking for is even on the map yet. In other words it is like using an old map. If you are a studier of maps like I happen to be, you will see the problem with older maps. Even some companies keep printing old map data year after year without adding in new on ramps, city streets, infrastructure freeway improvements and ring-roads, it is aggravating for those from out of town. Even more aggravating looking for an address or street in a new housing tract, which you can see but the devise insists, does not exist? Then there are problems in areas like Cape Coral, FL and Tehachapi, CA or El Paso, TX and Knoxville, TN where the roads have been scraped and ready to put in or put in but do not connect or have nothing there yet. Of course it is very aggravating to see a road and try to go down it and find it is a dirt road that connects to nothing yet or an entire sub-division that does not exist? Is it a Mirage? If so where is the white Tiger Show?

Jack Dangermond of ESRI had set up entire networks of software makers who developed data for their awesome software products for GPS and GIS needs. Used by government, military, utility companies, transportation companies, private companies with GPS units to sell to the public, First Responders and school districts for buses. After the Dot Com crash those software companies were among some of the survivors, but had significantly cut costs. Thus without the proper data the GPS systems bought by the upper, upper-middle and middle class for their cars were not always good enough to support the price point for the newest technology. This is especially upsetting since the upper, upper-middle and middle class citizens who pay the most taxes live in the suburbs for the most part. The chances of a middle class American; who bought a home during the 3 years last housing boom; not being able to find their house or street on their new GPS devise is a higher probability then them actually finding it. We interviewed one man who bought a new Nissan Sports car.

Who lives in a newer developed area in the higher end Las Vegas, Clark County Suburbs, which only had the main streets on his GPS and had huge blank spots on his device? Some GPS devices allow the user to choose a satellite vendor and data vendor and software, but many of the Factory units do not. People think they are getting something really good and then find they cannot use it to navigate, which would really piss you off considering you may have paid as much as $6,000 for the unit. Even more dangerous is the information we learned from an EMT ambulance driver in Dallas area who told us of looking for streets for 15-20 minutes after battling through suburban gridlock to get to where they thought it might be. 3G cell phone technology may assist for those using cell phones to call in data to the dispatches. For all the training we are doing across this nation for first responders and on-going education of police, fire, Hazmat, etc. it appears that we have forgotten the problems of the system. Any time you build a system to serve humankind you must make it simple and make it work, that should be the first, the very first priority, then you can fix all the other issues.

With that said we interviewed a lady recently one evening who had a hell of a long day working for the Metro Police Departments Central Nervous System. The communications center and dispatch is to what we are referring. Although she was unaware of the problem at the center for bad data or missing data in the system, she could not say how they were able to get the information. Luckily serving a metro area they are probably connected to the planning departments computer, which they should be. And if the police department has the new data and no problem in this case, why have the software vendors not been able to access the data? It is a safety issue if someone with a GPS system pulls out a map and tries to read it while driving in an area they are not familiar with. It is guaranteed that in the history of the automobile in this country more people have been in serious traffic accidents from trying to read maps, than talking on cell phones, although cell phones no doubt a contributing factor in many lesser accidents will eventually pass this figure. Where the streets are, well frankly I cannot understand the need to keep this a secret unless it is the layout of Area 51, Prison, Power plant, Pentagon grounds, Military Bases, etc. If the emergency first responders divisions and contractors would share the data, there might be less accidents and they maybe able to get some assistance from the public being the eyes and ears

http://www.lancewinslow.org/nmwp.shtml

and also perhaps they could in fact use the idea of Smart Virtual Mobile Communities or FlashMob scenarios since budgets are strapped as the National Security “Red-Orange-Yellow-High-Risk-Danger-Days” come with high frequency, more police and first responders are on duty and that costs money. Without significant inflows the coverage of the Grid of a city is in jeopardy of slower response times. Fast response times are the easiest way to keep the peace, everyone, which gets away can cause problems another day and of course in case of International Terrorist Attacks.

It is essential to have the data for these devises and everyone is better served when communication flows. GPS units provide that and the data should be readily available and probably it is best to have the cities using the same formats as first responders and the same data can be used for utilities, consumers, military and even census data or academia studying urban sprawl and growth rates to have infrastructures ready during expansion. Things like water and energy, which has obviously been a major focus here.

There needs to be a nationwide coordinated effort to see that such data is filtered into the private sector, because as it stand the companies have been hammered in the industry and cannot perform the services to bring this stuff to market. Communication is important for government and citizen a like, increased efficiencies in business will save the government money and provide additional tax base and funds on the income of such businesses utilizing such data, as well as save money and time for all the government services discussed above. If we want a screaming economy we ought to be thinking how we can streamline and accelerate the flow of information to increase efficiencies and allow a small portion of the gain from the expanded pie to continue the growth. In other words, we make it easier for the Florist to deliver, the school buses to pick up more kids per hour and the soccer mom to take more kids to practice and still have time left to shop all of which serves man. The digital GIS divide is as important for our economy as the Digital Internet Divide. Kids in sports do less drugs, become more competitive, have higher work ethics and soccer moms can help keep the retail economy going. Every time you ease the flow, more things are possible. The exponential increase in American productivity is needed to offset the time lost in traffic and congestion. GIS-GPS systems can help in any emergency or simply driving around town getting things done to check off one’s list for the day.



Source: http://ezinearticles.com/?GPS-Navigation-Systems-and-Data-Problems&id=27265

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

Web Scraping for SEO with these Open-Source Scrapers

When conducting Search Engine Optimization (SEO), we’re required to scrape websites for data, our campaigns, and reports for our clients. At the lowest level we utilize scraping to keep track of rankings on search engines like Google, Bing, and Yahoo, even keep a track of links on websites to know when it’s completed its lifespan. Then we’ve used them to help us aggregate data from APIs, RSS feeds, and websites to conduct some of our data mining to find patterns to help us become more competitive.  So scraping is a function majority of companies(SEOmoz, Raventools, and Google) have to do to either save money, protect intellectual property, track trends, etc… Businesses can find infinite uses with scraping tools, it just depends if you’re an printed circuit board manufacturer looking for ideas on your e-mail marketing campaign or a Orange County based business trying to keep an eye out on the competition. which is why we’ve created a comprehensive list of open source scrapers out there to help all the businesses out there. Just keep in mind we haven’t used all of them!

Words of caution, web scrapers require knowledge specific to the language such as PHP & cURL. Take into considerations issues like cookie management, fault tolerance, organizing the data properly, not crashing the website being scraped, and making sure the website doesn’t prohibit scraping.

If you’re ready, here’s the list…


Source: http://www.annexcore.com/blog/web-scraping-for-seo-with-these-open-source-scrapers/

Assuring Scraping Success with Proxy Data Scraping

Have you ever heard of "Data Scraping?" Data Scraping is the process of collecting useful data that has been placed in the public domain of the internet (private areas too if conditions are met) and storing it in databases or spreadsheets for later use in various applications. Data Scraping technology is not new and many a successful businessman has made his fortune by taking advantage of data scraping technology.

Sometimes website owners may not derive much pleasure from automated harvesting of their data. Webmasters have learned to disallow web scrapers access to their websites by using tools or methods that block certain ip addresses from retrieving website content. Data scrapers are left with the choice to either target a different website, or to move the harvesting script from computer to computer using a different IP address each time and extract as much data as possible until all of the scraper's computers are eventually blocked.

Thankfully there is a modern solution to this problem. Proxy Data Scraping technology solves the problem by using proxy IP addresses. Every time your data scraping program executes an extraction from a website, the website thinks it is coming from a different IP address. To the website owner, proxy data scraping simply looks like a short period of increased traffic from all around the world. They have very limited and tedious ways of blocking such a script but more importantly -- most of the time, they simply won't know they are being scraped.

You may now be asking yourself, "Where can I get Proxy Data Scraping Technology for my project?" The "do-it-yourself" solution is, rather unfortunately, not simple at all. Setting up a proxy data scraping network takes a lot of time and requires that you either own a bunch of IP addresses and suitable servers to be used as proxies, not to mention the IT guru you need to get everything configured properly. You could consider renting proxy servers from select hosting providers, but that option tends to be quite pricey but arguably better than the alternative: dangerous and unreliable (but free) public proxy servers.

There are literally thousands of free proxy servers located around the globe that are simple enough to use. The trick however is finding them. Many sites list hundreds of servers, but locating one that is working, open, and supports the type of protocols you need can be a lesson in persistence, trial, and error. However if you do succeed in discovering a pool of working public proxies, there are still inherent dangers of using them. First off, you don't know who the server belongs to or what activities are going on elsewhere on the server. Sending sensitive requests or data through a public proxy is a bad idea. It is fairly easy for a proxy server to capture any information you send through it or that it sends back to you. If you choose the public proxy method, make sure you never send any transaction through that might compromise you or anyone else in case disreputable people are made aware of the data.

A less risky scenario for proxy data scraping is to rent a rotating proxy connection that cycles through a large number of private IP addresses. There are several of these companies available that claim to delete all web traffic logs which allows you to anonymously harvest the web with minimal threat of reprisal. Companies such as http://www.Anonymizer.com offer large scale anonymous proxy solutions, but often carry a fairly hefty setup fee to get you going.

The other advantage is that companies who own such networks can often help you design and implementation of a custom proxy data scraping program instead of trying to work with a generic scraping bot. After performing a simple Google search, I quickly found one company (www.ScrapeGoat.com) that provides anonymous proxy server access for data scraping purposes. Or, according to their website, if you want to make your life even easier, ScrapeGoat can extract the data for you and deliver it in a variety of different formats often before you could even finish configuring your off the shelf data scraping program.

Whichever path you choose for your proxy data scraping needs, don't let a few simple tricks thwart you from accessing all the wonderful information stored on the world wide web!


Source: http://ezinearticles.com/?Assuring-Scraping-Success-with-Proxy-Data-Scraping&id=248993