Data Collection, Just Another Way To Gather Information

Data collection just does not help the companies to launch new products or know about the public reaction to a specific issue, it is a very useful tool for statistical inferences, once the collected data is compiled. The process of data collection is the third step of the six step market research processes. Data collection can be done in two ways involving various technicalities. In this article, we shall give a brief overview of the same.

Data collection can be done in two ways - secondary data and primary data. Secondary data collection involves is the information available in books, journals, previous researches or studies and the Internet. It basically involves making use of the data already present to build or substantiate a concept.

On the other hand, primary data collection is the process of data collection through questionnaire by directly asking respondents of their opinions. Forming the right questionnaire is the most important aspect of data collection. The researcher conducting the data collection just has to be aware of the process. He should have a clear idea about the information sought by the concerned party.

Besides, the data collection officer should be able to construct the questionnaire in such a way so as to elicit the responses needed. Having constructed the questionnaire the researcher should identify the target sample. To illustrate the point clearly, we shall look into the following example.

Suppose, data collection is aimed from an area A, then, if all the residents of the data are given the questionnaire, it is called a census or in other words data collection is done from all the individuals of the specified area. One of the most common examples of data collection done by the government is census. For example the population census conducted by the US Census Bureau every ten years. On the other hand, if only twenty or thirty percent of the population living in area A are given the questionnaire, the mode of data collection would be called sampling.

The data collected from the target sample with a well-defined questionnaire will project the response of the entire population living in the area. Data collected from a sample helps to control the cost and time spent on collecting data from the population. Sample is a part of population.

Data collection just gets easier from the target sample with the help of a pretested questionnaire, which is later analyzed using statistical tests like ANOVA, Chi Square test and so on. These tests help the researcher to infer the result obtained from the data collection.

Market research/data collection is a fast growing and lucrative career option now days. One has to undertake a course in marketing, statistics and research before starting out. It is indeed very important to have a through understanding of various concepts and the theories related. Some basic terminologies related to data collection are: census, incidence, sample, population, parameters, sampling frames and so on.

Source: http://ezinearticles.com/?Data-Collection,-Just-Another-Way-To-Gather-Information&id=853158

How Easily Can You Extract Data From Web

How Easily Can You Extract Data From Web

With tech advancements taking the entire world by a storm, every sector is undergoing massive transformations. As far as the business arena is concerned, the rise of big data and data analytic is playing a crucial part in operations. Big data and data analysis is the best way to identify customer interests. Businesses can gain crystal clear insights into consumers’ preferences, choices, and purchase behaviours, and that’s what leads to unmatched business success. So, it’s here that we come across a crucial question. How do enterprises and organisations leverage data to gain crucial insights into consumer preferences? Well, data extraction and mining are the two significant processes in this context. Let’s take a look at what data extraction means as a process.

Decoding data extraction

Businesses across the globe are trying their best to retrieve crucial data. But, what is it that’s helping them do that? It’s here that the concept of data extraction comes into the picture. Let’s begin with a functional definition of this concept. According to formal definitions, ‘data extraction’ refers to the retrieval of crucial information through crawling and indexing. The sources of this extraction are mostly poorly-structured or unstructured data sets. Data extraction can prove to be highly beneficial if done in the right way. With the increasing shift towards online operations, extracting data from the web has become highly important.

The emergence of ‘scraping’

The act of information or data retrieval gets a unique name, and that’s what we call ‘data scraping.’ You might have already decided to pull data from 3rd party websites. If that’s what it is, then it’s high time to embark on the project. Most of the extractors will begin by checking the presence of APIs. However, they might be unaware of a crucial and unique option in this context.

Automatic data support

Every website lends virtual support to a structured data source, and that too by default. You can pull out or retrieve highly relevant data directly from the HTML. The process is termed as ‘web scraping’ and can ensure numerous benefits for you. Let’s check out how web scraping is useful and awesome.

Any content you view is ready for scraping

All of us download various stuff throughout the day. Whether it is music, important documents or images, downloads seem to be regular affairs. When you are successful in downloading any particular content of a page, it means the website offers unrestricted access to your browser. It won’t take long for you to understand that the content is programmatically accessible too. On that note, it’s high time to work out effective reasons that define the importance of web scraping. Before opting for RSS feeds, APIs, or other conventional data extraction methods, you should assess the benefits of web scraping. Here’s what you need to know in this context.

Website vs. APIs: Who’s the winner?

Site owners are more concerned about their public-facing or official websites than the structured data feeds. APIs can change, and feeds can shift without prior notifications. The breakdown of Twitter’s developer ecosystem is a crucial example for this.

So, what are the reasons for this downfall?

At times, these errors are deliberate. However, the crucial reasons are something else. Most of the enterprises are completely unaware of their structured data and information. Even if the data gets damaged, altered, or mangled, there’s no one to care about it.

However, that isn’t what happens with the website. When an official website stops functioning or delivers poor performance, the consequences are direct and in-your-face. Quite naturally, developers and site owners decide to fix it almost instantaneously.

Zero-rate limiting

Rate-limiting doesn’t exist for public websites. Although it’s imperative to build defences against access automation, most of the enterprises don’t care to do that. It’s only done if there are captchas on signups. If you aren’t making repeated requests, there are no possibilities of you being considered as a DDOS attack.

In-your-face data

Web scraping is perhaps the best way to gain access to crucial data. The desired data sets are already there, and you won’t have to rely on APIs or other data sources for gaining access. All you need to do is browse the site and find out the most appropriate data. Identifying and figuring out the basic data patterns will help you to a great extent.

Unknown and Anonymous access

You might want to gather information or collect data secretly. Simply put, you might wish to keep the entire process highly confidential. APIs will demand registrations and give you a key, which is the most important part of sending requests. With HTTP requests, you can stay secure and keep the process confidential, as the only aspects exposed are your site cookies and IP address. These are some of the reasons explaining the benefits of web scraping. Once you are through with these points, it’s high time to master the art of scraping.

Getting started with data extraction

If you are already eager to grab data, it’s high time you work on the blueprints for the project. Surprised? Well, data scraping or rather web data scraping requires in-depth analysis along with a bit of upfront work. While documentations are available with APIs, that’s not the case with HTTP requests. Be patient and innovative, as that will help you throughout the project.

2. Data fetching

Begin the process by looking for the URL and knowing the endpoints. Here are some of the pointers worth considering:

- Organized information: You must have an idea of the kind of information you want. If you wish to have it in an organized manner, rely on the navigation offered by the site. Track the changes in the site URL while you click through sections and sub-sections.
- Search functionality: Websites with search functionality will make your job easier than ever. You can keep on typing some of the useful terms or keywords based on your search. While doing so, keep track of URL changes.
- Removing unnecessary parameters: When it comes to looking for crucial information, the GET parameter plays a vital role. Try looking for unnecessary and undesired GET parameters in the URL, and removing them from the URL. Keep the ones that’ll help you load the data.

2. Pagination comes next

While looking for data, you might have to scroll down and move to subsequent pages. Once you click to Page 2, ‘offset=parameter’ gets added to the selected URL. Now, what is this function all about? The ‘offset=parameter’ function can represent either the number of features on the page or the page-numbering itself. The function will help you perform multiple iterations until you attain the “end of data” status.

Trying out AJAX

Most of the people nurture certain misconceptions about data scraping. While they think that AJAX makes their job tougher than ever, it’s actually the opposite. Sites utilising AJAX for data-loading ensures smooth data scraping. The time isn’t far away when AJAX will return along with JavaScript. Pulling up the ‘Network’ tab in Firebug or Web Inspector will be the best thing to do in this context. With these tips in mind, you will have the opportunity to get crucial data or information from the server. You need to extract the information and get it out of the page markup, which is the most difficult or tricky part of the process.

Unstructured data issues

When it comes to dealing with unstructured data, you will need to keep certain crucial aspects in mind. As stated earlier, pulling out the data from page markups is a highly critical task. Here’s how you can do it:

1. Utilising the CSS hooks

According to numerous web designers, the CSS hooks happen to be the best resources for puling data. Since it doesn’t involve numerous classes, CSS hooks offer straightforward data scraping.

2. Good HTML Parsing

Having a good HTML library will help you in ways more than one. With the help of a functional and dynamic HTML parsing library, you can create several iterations as and when you wish to.
Knowing the loopholes

Web scraping won’t be an easy affair. However, it won’t be a hard nut to crack either. While knowing the crucial web scraping tips is necessary, it’s also imperative to get an idea of the traps. If you have been thinking about it, we have something for you!

- Login contents: Contents that require you to login might prove to be potential traps. It reveals your identity and wreaks havoc on your project’s confidentiality.

- Rate limiting: Rate limiting can affect your scraping needs both positively and negatively, and that entirely depends on the application you are working on.

Source:-https://www.promptcloud.com/blog/how-easy-is-data-extraction

A guide to data scraping

Data is all the rage these days.

It’s what businesses are utilizing to create an unfair advantage with their customers. The more data you acquire, the easier it becomes to slice it up in a unique way to solve problems for your customers.

But knowing that data can benefit you – and actually getting the data – are two separate items.
Much like technology, data can catapult you to greater heights, or it can bring you to your knees.
That’s why it is essential to pay careful attention and ensure the data you use propels you forward versus holding you back.

Why all data isn’t created equal

The right data can make you a hero. It can keep you at the forefront of your industry, allowing you to use the insights the information uncovers to make better decisions.

Symphony Analytics uses a myriad of patient data from a variety of sources to develop predictive models, enabling them to tailor medication schedules for different patient populations.

Conversely, the wrong data can sink you. It can cause you to take courses of action that just aren’t right. And, if you take enough wrong action based upon wrong data, your credibility and reputation could suffer a blow that’s difficult to recover from.

For instance, one report from the state of California auditor’s office shows that accounting records were off by more than $6 million due to flawed data.

That’s no good. And totally avoidable.

As a result, it is critical you invest the energy in advance to ensure the data you source will make you shine, rather than shrink.
How to get good data

You’ve got to plan for it. You’ve got to be clear about your business objectives, and then you’ve got to find a way to source the information in a consistent and reliable manner.

If your business’ area of expertise is data capture and analysis, then gathering the information you need on your own could be a viable option.

But, if the strength of you and your team isn’t in this specialized area, then it’s best to leave it to the professionals.

That’s why brands performing market research on a larger scale often hire market research firms to administer the surveys, moderate focus groups or conduct one-on-one interviews.

Of late, more companies are turning to data scraping as a means to capture the quantitative information they need to fuel their businesses. And they frequently turn to third-party companies to supply them with the information they need.

While doing so allows them to focus on their core businesses, relinquishing control of a critical asset for their businesses can be a little nerve-racking.

But, it doesn’t have to be. That is if you work with the right data scraping partner.

How to choose the right data scraping partner for you
In the project management world, there’s a triangle that is often used to help prioritize what is most important to you when completing a task.

Data Scraping Group: Good, Fast, Cheap - Pick any two

Although you may want all three choices, you can only pick two.

If you want something done fast, and of good quality, know that it won’t be cheap. If you want it fast and cheap, be aware that you will sacrifice quality. And if you’d like it to be cheap and good, prepare to wait a bit, because speed is a characteristic that will fall off the table.

There are many 3rd party professionals who can offer data scraping services for you. As you begin to evaluate them, it will be helpful to keep this triangle in mind.
Here are six considerations when exploring a partner to work with to ensure you get high-quality
web crawling and data extraction.

1. How does the data fit into your business model?

This one is counter intuitive, but it’s a biggie. And, it plays a major role as you evaluate all the other considerations.

If the data you are receiving is critical to your operations, then obtaining high-quality information exactly when you need it is non-negotiable. Going back to the triangle, “good” has to be one of your two priorities.

For instance, if you’re a daily deal site, and you rely on a third party to provide you all the data for the deals, then having screw-ups with your records just can’t happen.
That would be like a hospital not staffing doctors for the night. It just doesn’t work.
But, if the data you need isn’t mission critical for you to run your business, you may have a little more leeway in terms of how you weight the other factors that go into choosing who best to work with.

2. Cost

A common method numerous businesses use to evaluate costs is just to evaluate vendors based on the prices they quote.

And, too often, companies let the price ranges of the service providers dictate how much they are willing to pay.

A smarter option is to determine your budget in advance … before you even go out to explore who can get you the data you need. Specifically, you should decide how much you are able and willing to pay for the information you want. Those are two different issues.
Most businesses don’t enjoy unlimited budgets. And, even when the information being sourced is critical to operating the business, there is still a ceiling for what you’re able to pay.
This will help you start operating from a position of strength, rather than reacting to the quotes you may receive.

Another thing to consider are the various types of fees. Some companies charge a setup fee, followed by a subsequent monthly fee. Others charge fixed costs. If you’re looking at multiple quotes from vendors, this could make it difficult for you to compare.
A wise way to approach this is to make sure you are clear on what the total cost would be for the project, for whatever specified time period you’d like to contract with someone.
Here are a few questions to ask to make sure you get a full view of the costs and fees in the estimate:

-Is there a setup fee?
-What are the fixed costs associated with this project?
-What are the variable costs, and how are they calculated?
-Are there any other taxes, fees, or things that I could be charged for that are not listed on this quote?
-What are the payment terms?

3. Communication

Even when you’ve got a foolproof system that runs like a well-oiled machine, you still need to interact with your vendors on a regular basis. Ongoing communication confirms things are operating the way you’d like, gives you an opportunity to discuss possible changes and ensures your partner has a firm understanding of your business needs.

The data you are sourcing is important to you and your business. You need to partner with someone who will be receptive to answering questions and responding in a timely manner to inquiries you have.

4. Reputation

This was mentioned before, but it’s worth repeating. All data is not created equal. And, if you are utilizing data as a means to build and grow your business, you need to make sure it’s good.

So, even though data scraping isn’t your area of expertise, it will greatly benefit you to spend time validating the reputation the people vying to deliver it to you.

How do they bake quality in their work? Do they have any certifications or other forms of proof to give you further confidence in their capabilities? Have their previous customers been pleased with the quality of the data they’ve delivered?

You could do so by checking reviews of previous customers to see how pleased they were and why. This method is also helpful because it may assist you in identifying other important criteria that may not have been on your radar.

You could also compare the credentials of each of the vendors, and the teams who will actually be working on your project.

Another highly-effective way could be to simply spend time talking to your potential partners and have them explain to you their processes. While you may not understand all the lingo, you could ask them a few questions about how they engage in quality control and see how they respond.

You’d probably be shocked at the range of answers you get.

Here are a few questions to guide you as you start asking questions about their quality system:

- Are the data spiders customized for the websites you want information from?
- What mechanisms are in place to verify the harvested data is correct?
- How is the performance of the data spiders monitored to verify they haven’t failed?
- How is the data backed up? Is redundancy built into the process so that information is not lost?
- Is internet access high-speed, and how frequently is it monitored?

5. Speed

For those suppliers that are able to deliver data to you fast, make sure you understand why they are able to deliver at such a rapid speed. Are there special systems they have in place that enable them to do so? Or perhaps, is there any level of quality that is sacrificed as a result of getting you information fast.

Often when contracting with a data extraction partner, they’ll deliver your information on a set schedule that you both agree upon.

But, there may be times when you need information outside of your normal schedule, and you may even need it on a brief timeline.

Knowing in advance how quickly your partner is able to turn around a request will help you better prepare project lead times.

6. Scalability

The needs of your business change over time. And, as you work to grow, it is quite possible the data needs of your company will expand as well.

So, it’s helpful to know your data scraping partner is able to grow with you. It would be great to know that as the volume, and perhaps the speed of the information you need to run your business increases, the company providing it is able to keep pace.

Don’t get stuck with bad data
It could spell disaster for your business. So, make sure you do your due diligence to fully vet the companies you’re considering sourcing your data from.
Make a list of requirements in advance and rank them, if necessary, in order of importance to you.
That way, as you begin to evaluate proposals and capabilities, you’ll be in a position to make an informed decision.
You need good data. Your customers need you to have good data, too.
Make sure you work with someone who can give it to you.

Source url :-http://www.data-scraping.com.au/techniques-for-high-quality-web-crawling-and-data-extraction

Things to Factor in while Choosing a Data Extraction Solution

Things to Factor in while Choosing a Data Extraction Solution

Customization options

You should consider how flexible the solution is when it comes to changing the data points or schema as and when required. This is to make sure that the solution you choose is future-proof in case your requirements vary depending on the focus of your business. If you go with a rigid solution, you might feel stuck when it doesn’t serve your purpose anymore. Choosing a data extraction solution that’s flexible enough should be given priority in this fast-changing market.

Cost

If you are on a tight budget, you might want to evaluate what option really does the trick for you at a reasonable cost. While some costlier solutions are definitely better in terms of service and flexibility, they might not be suitable for you from a cost perspective. While going with an in-house setup or a DIY tool might look less costly from a distance, these can incur unexpected costs associated with maintenance. Cost can be associated with IT overheads, infrastructure, paid software and subscription to the data provider. If you are going with an in-house solution, there can be additional costs associated with hiring and retaining a dedicated team.

Data delivery speed

Depending on the solution you choose, the speed of data delivery might vary hugely. If your business or industry demands faster access to data for the survival, you must choose a managed service that can meet your speed expectations. Price intelligence, for example is a use case where speed of delivery is of utmost importance.

Dedicated solution

Are you depending on a service provider whose sole focus is data extraction? There are companies that venture into anything and everything to try their luck. For example, if your data provider is also into web designing, you are better off staying away from them.

Reliability

When going with a data extraction solution to serve your business intelligence needs, it’s critical to evaluate the reliability of the solution you are going with. Since low quality data and lack of consistency can take a toll on your data project, it’s important to make sure you choose a reliable data extraction solution. It’s also good to evaluate if it can serve your long-term data requirements.

Scalability

If your data requirements are likely to increase over time, you should find a solution that’s made to handle large scale requirements. A DaaS provider is the best option when you want a solution that’s salable depending on your increasing data needs.

When evaluating options for data extraction, it’s best keep these points in mind and choose one that will cover your requirements end-to-end. Since web data is crucial to the success and growth of businesses in this era, compromising on the quality can be fatal to your organisation which again stresses on the importance of choosing carefully.

Source:https://www.promptcloud.com/blog/choosing-a-data-extraction-service-provider

4 Tools That Makes Web Data Extraction Easy

There is a huge amount of data available on the World Wide Web. Organizations and individuals find this information useful and often have to make use of it for various purposes. Traditionally, web data is retrieved by browsing and keyword searching. These methods are purely intuitive, the searches can return vast amount of unnecessary data, and it can take quite a bit of time before the searchers find what they are looking for. This data is sometimes hard to manipulate and work on as it is done in traditional databases.

But web pages written in mark-up languages like HTML and XHTML contain a wealth of knowledge. They also provide the structures that make data manipulation and analysis so easy. To extract this data some easily usable applications have been built. Though people who know nothing about coding can use some of these applications, it is always advisable to take the help of data extraction experts for help with such work, to obtain best results.

4  Tools to Improve your Web Data Extraction Efforts:

Uipath:

One of the popular web scraping applications is offered by the software automation and application integration company, Uipath. They offer free trials and also live demos for new users and potential customers. They offer website scraping from HTML, XML, AJAX, Java applets, Flash, Silverlight and PDF. Their application has powerful data transformation features and enables deduplication with SQL and LINQ queries.
Once the data has been extracted, it can be exported to various outputs like Microsoft Excel, CSV, .NET DataTable and so on. Automations can be done with web login, navigation, and even filling of forms.
This application is good for non-coders and can even be used to manipulate the interface of another application so that data transfer can take place between the two of them.
The price tag might be a tad high for individual users, but is worth it if you want a fast, accurate and simple application.

Import.io:

 Import.io offers to “instantly turn web pages into data”. They advertise their service saying that the customer does not need plugin, training or setup. Users can create custom APIs and crawl entire websites by using their desktop application. The best part is that no coding knowledge is required. Users can scrap data from an unlimited number of web pages. For the service, each page is a source that holds great potential to source application programming interface.
The extracted data is stored on Import.io’s cloud servers. It can then be downloaded in different formats that include CSV, Google sheets, Microsoft Excel and many more. The generated API enables users to integrate live web data with their own applications, third party analytics and visualization software without much difficulty. Though users do not need much technical skills to operate this service, the extraction reports arrives a good 24 hours after the request has been submitted.

Kimono:

The task of building an API to power applications, models and visualizations using live data and without the benefit of any code is done in seconds by Kimono. The service has a smart extractor. It recognizes patterns in web content. This enables the user to get the data that he or she wants, quickly and visually. The extracted APIs are hosted on a cloud. They are then run as per the schedule that is convenient for the user. While there is no problem with either the speed or the accuracy of Kimono, there is a lack of availability of page navigation, and the system requires some training before it begins to function at full capability.

Screen Scraper:

Like the other above-mentioned services, Screen Scraper works well with HTML and Javascript, extracts data precisely and provides the data in Excel and CSV fomat. However, it requires the user to have some coding skills. Only then can it be used to its optimum functionality. Even though the user will have to shell out a bit of money to use Screen Scraper, the service can handle almost any data extraction task with ease.

Source Url:-https://www.invensis.net/blog/data-processing/4-tools-makes-web-data-extraction-easy/

Web scraping techniques

Web scraping techniques

There can be various ways of accessing the web data. Some of the common techniques are using API, using the code to parse the web pages and browsing. The use of API is relevant if the site from where the data needs to be extracted supports such a system from before. Look at some of the common techniques of web scraping.

1. Text greping and regular expression matching

It is an easy technique and yet can be a powerful method of extracting information or data from the web. However, the web pages then need to be based on the grep utility of the UNIX operating system for matching regular expressions of the widely used programming languages. Python and Perl are some such programming languages.

2. HTTP programming

Often, it can be a big challenge to retrieve information from both static as well as dynamic web pages. However, it can be accomplished through sending your HTTP requests to a remote server through socket programming. By doing so, clients can be assured of getting accurate data, which can be a challenge otherwise.

3. HTML parsers

There are few data query languages in a semi-structured form that are capable of including HTQL and XQuery. These can be used to parse HTML web pages thus fetching and transforming the content of the web.

4. DOM Parsing

When you use web browsers like Mozilla or Internet Explorer, it is possible to retrieve contents of dynamic web pages generated by client scripting programs.

5. Reorganizing the semantic annotation

There are some web scraping services that can cater to web pages, which embrace metadata markup or semantic. These may be meant to track certain snippets. The web pages may embrace the annotations and can be also regarded as DOM parsing.
Setup or configuration needed to design a web crawler

The below-mentioned steps refer to the minimum configuration, which is required for designing a web scraping solution.

HTTP Fetcher– The fetcher extracts the web pages from the site servers targeted.

Dedup– Its job is to prevent extracting duplicate content from the web by making sure that the same text is not retrieved multiple times.

Extractor– This is a URL retrieval solution to fetch information from multiple external links.

URL Queue Manager– This queue manager puts the URLs in a queue and assigns a priority to the URLS that needs to be extracted and parsed.

Database– It is the place or the destination where data after being extracted by a web scraping tool is stored to process or analyze further.

Advantages of Data as a Service Providers

Outsourcing the data extraction process to a Data Services provider is the best option for businesses as it helps them focus on their core business functions. By relying on a data as a service provider, you are freed from the technically complicated tasks such as crawler setup, maintenance and quality check of the data. Since DaaS providers have expertise in extracting data and a pre-built infrastructure and team to take complete ownership of the process, the cost that you would incur will be significantly less than that of an in-house crawling setup.

Key advantages:

- Completely customisable for your requirement
- Takes complete ownership of the process
- Quality checks to ensure high quality data
- Can handle dynamic and complicated websites
- More time to focus on your core business

Source:https://www.promptcloud.com/blog/commercial-web-data-extraction-services-enterprise-growth

How Web Scraping Software Can be Beneficial For Your Business

How Web Scraping Software Can be Beneficial For Your Business

Web scraping is the process of extracting information from different websites using several coded software programs. Best web scraping software can stimulate the human exploration of the web through different methods including embedding web browsers, Internet Explorer or implementing Hyper Text Transfer Protocol (HTTP).

Web scraping softwares focus on extracting data like product prices, weather information, public records (Unclaimed Money, Criminal records, Sex Offenders, Court records), retail store locations, or stock price movements; in a local database for further use. They can offer several advantages to the business firms by extracting data accurately, productively and in a short time. The other attributes of this efficient tool includes:

#   No Expensive Errors- Web scrapping can eliminate high-priced errors by reducing the demand for human interaction in the data extraction process, no matter how complicated or huge.

#   Automated Data Collection- With an automated data extraction application, you can get accurate information and can eliminate data entry costs.

#   Saves you time- Extracting information manually can be a time consuming process. But, with data harvesting softwares, you can gather the details in a short time and can focus on other core business activities.

#   Innovative Techniques- New characteristics and advanced extraction methods formed are made accessible immediately.

#   Supervisor your competitor's activities- With these web scraping methods, you can easily acquire the information from your competitors, like their products, value, and other essential details as and when updated on their online catalog.

#   No Third party applications- Companies offering best web scraping software services can eliminate the need to buy any specific software.

#   Gain competitive edge- With these extracting tools, you can speedily get vital information; thereby giving you an edge over the competition.

There are many companies offering best web scraping software services at affordable prices. Make your search on the web to get the details of these service providers. Internet is the best medium to get the details on any topic. You can even ask your known ones who have availed these services recently to know his experience with the service providers. Compare the prices offered by different companies to choose the best one that can cover your needs within budget. Web data extracting professionals are expert in harvesting data from different resources by forming non-intrusive customized data scraping solutions. They can take care of the different data extraction needs of the individuals and provide them with raw and accurate data in the short time and by making least effort on their part, thereby allowing them to focus on their core business.

Their efficient and influential web scraping services use proprietary algorithms made to extract and convert unstructured content into structured data(like HTML format) that can be stored and analyzed in a local database.

Hire the best company for web scraping services. These softwares can provide several benefits for your business like online lead generation, weather data monitoring, price comparison with your competition, website change detection, Web content mashup, Web research, and Web data integration.

Get in touch to take the benefits of our exceptional services at cost-effective prices.

Source:http://www.sooperarticles.com/internet-articles/affiliate-programs-articles/how-web-scraping-software-can-beneficial-your-business-1460101.html#ixzz4hmvy0oRL

Web scraping provides reliable and up-to-date web data

Web scraping provides reliable and up-to-date web data

There is an inconceivably vast amount of content on the web which was built for human consumption. However, its unstructured nature presents an obstacle for software. So the general idea behind web scraping is to turn this unstructured web content into a structured format for easy analysis.

Automated data extraction smooths the tedious manual aspect of research and allows you to focus on finding actionable insights and implementing them. And this is especially critical when it comes to online reputation management. Respondents to The Social Habit study showed that when customers contact companies through social media for customer support issues, 32% expect a response within 30 minutes and 42% expect a response within 60 minutes. Using web scraping, you could easily have constantly updating data feeds that alert you to comments, help queries, and complaints about your brand on any website, allowing you to take instant action.

You also need to be sure that nothing falls through the cracks. You can easily monitor thousands, if not millions of websites for changes and updates that will impact your company.

Source:https://blog.scrapinghub.com/2016/12/15/how-to-increase-sales-with-online-reputation-management/

Understanding URL scraping

Understanding URL scraping

URL scraping is the process where you automatically extract and filter URLs of WebPages that have specific features. The features that you are looking for vary depending on your goal. For example, if you are looking for a site where you can place your comment and get back link juice, you should go for WebPages that allow dofollow comments.

Techniques for URL scraping

There are many techniques that you can use to get the URL that you are looking for. Some of these techniques include:

Copy pasting: this is where you visit a given site and check whether it has the features that you are looking for. For example, if you are interested in dofollow links, you should visit a number of sites and find out if they have your target links. You should then identify the ones that have the features that you are looking for and compile a list.

Text grepping: this is a technique that allows you to search plain text on websites that match a regular expression. Although, the technique was designed for Unix, you can also use it on other operating systems.

HTTP programming: here you retrieve the WebPages that have the features that you are looking for. You should then note the URL of the pages. To retrieve the pages you have to post HTTP requests using a remote server that uses socket programming.

HTML Parser: a HTML parser allows you to mine data by detecting a common template, script or code on a specific website or Webpage. To be able to detect the script or code you have to use one of the many programming languages: HTQL, Java, PHP, XQuery and Python. Once the data is extracted, it's translated and packaged in a way that you are able to easily understand it.

DOM parsing: This is a technique where you retrieve dynamic content that has been generated by client side scripts that execute in a web browser such as Google Chrome, Mozilla Firefox or any other browsers.

URL scraping software: this is the easiest way of scraping URLs as all you need is high quality software that will do all the work for you. You should identify the features that you are interested in and then give command to the software. The software will go through all the sites on the internet and extract the URLs of the pages that have your target features.

We have plenty of information on CPV and Internet Marketing; therefore, if you are looking for URL Scraper tools for PPV you should highly consider visiting our website.

Source:http://www.amazines.com/article_detail.cfm/6180373?articleid=6180373

How Web Scraping Services Help Businesses to Do Better?

How Web Scraping Services Help Businesses to Do Better?

Web scraping services help in growing business as well as reaching business to the new success and heights. Data scraping services is the procedure to extract data from the websites like eBay for different business requirements. This gives high quality and accurate data which serves all your business requirements, track your opponents and convert you into decision maker. In addition, eBay web scraping services offer you data in the customized format and extremely cost effective too. It gives you easy way in of website data in the organized and resourceful manner that you can utilize the data for taking knowledgeable decision which is very important for the business.

Also, it creates new opportunities for monetizing online data as well as really suitable for the people that want to begin with lesser investment yet dreaming about enormous success of their business. Other advantages of eBay web scraping services include Lead Generation, Price Comparison, Competition Tracking, Consumer Behavior Tracking, and Data for online stores.

Data Extraction can be defined as the process of retrieving data from an unstructured source in order to process it further or store it. It is very useful for large organizations who deal with large amount of data on a daily basis that need to be processed into meaningful information and stored for later use. The data extraction is a systematic way to extract and structure data from scattered and semi-structured electronic documents, as found on the web and in various data warehouses.

In today's highly competitive business world, vital business information such as customer statistics, competitor's operational figures and inter-company sales figures play an important role in making strategic decisions. By signing on this service provider, you will be get access to critivcal data from various sources like websites, databases, images and documents.

It can help you take strategic business decisions that can shape your business' goals. Whether you need customer information, nuggets into your competitor's operations and figure out your organization's performance, it is highly critical to have data at your fingertips as and when you want it. Your company may be crippled with tons of data and it may prove a headache to control and convert the data into useful information. Data extraction services enable you get data quickly and in the right format.

Source:http://ezinearticles.com/?Data-Extraction-Services-For-Better-Outputs-in-Your-Business&id=2760257

Data Mining Basics

Definition and Purpose of Data Mining:

Data mining is a relatively new term that refers to the process by which predictive patterns are extracted from information.
Data is often stored in large, relational databases and the amount of information stored can be substantial. But what does this data mean? How can a company or organization figure out patterns that are critical to its performance and then take action based on these patterns? To manually wade through the information stored in a large database and then figure out what is important to your organization can be next to impossible.This is where data mining techniques come to the rescue! Data mining software analyzes huge quantities of data and then determines predictive patterns by examining relationships.

Data Mining Techniques:

There are numerous data mining (DM) techniques and the type of data being examined strongly influences the type of data mining technique used.Note that the nature of data mining is constantly evolving and new DM techniques are being implemented all the time.Generally speaking, there are several main techniques used by data mining software: clustering, classification, regression and association methods.

Clustering:

Clustering refers to the formation of data clusters that are grouped together by some sort of relationship that identifies that data as being similar. An example of this would be sales data that is clustered into specific markets.

Classification:

Data is grouped together by applying known structure to the data warehouse being examined. This method is great for categorical information and uses one or more algorithms such as decision tree learning, neural networks and "nearest neighbor" methods.

Regression:

Regression utilizes mathematical formulas and is superb for numerical information. It basically looks at the numerical data and then attempts to apply a formula that fits that data.New data can then be plugged into the formula, which results in predictive analysis.

Association:

Often referred to as "association rule learning," this method is popular and entails the discovery of interesting relationships between variables in the data warehouse (where the data is stored for analysis). Once an association "rule" has been established, predictions can then be made and acted upon. An example of this is shopping: if people buy a particular item then there may be a high chance that they also buy another specific item (the store manager could then make sure these items are located near each other).

Data Mining and the Business Intelligence Stack:

Business intelligence refers to the gathering, storing and analyzing of data for the purpose of making intelligent business decisions. Business intelligence is commonly divided into several layers, all of which constitute the business intelligence "stack."
The BI (business intelligence) stack consists of: a data layer, analytics layer and presentation layer.The analytics layer is responsible for data analysis and it is this layer where data mining occurs within the stack. Other elements that are part of the analytics layer are predictive analysis and KPI (key performance indicator) formation.Data mining is a critical part of business intelligence, providing key relationships between groups of data that is then displayed to end users via data visualization (part of the BI stack's presentation layer). Individuals can then quickly view these relationships in a graphical manner and take some sort of action based on the data being displayed.

Source: http://ezinearticles.com/?Data-Mining-Basics&id=5120773

Three Common Methods For Web Data Extraction

Three Common Methods For Web Data Extraction

Probably the most common technique used traditionally to extract data from web pages this is to cook up some regular expressions that match the pieces you want (e.g., URL's and link titles). Our screen-scraper software actually started out as an application written in Perl for this very reason. In addition to regular expressions, you might also use some code written in something like Java or Active Server Pages to parse out larger chunks of text. Using raw regular expressions to pull out the data can be a little intimidating to the uninitiated, and can get a bit messy when a script contains a lot of them. At the same time, if you're already familiar with regular expressions, and your scraping project is relatively small, they can be a great solution.

Other techniques for getting the data out can get very sophisticated as algorithms that make use of artificial intelligence and such are applied to the page. Some programs will actually analyze the semantic content of an HTML page, then intelligently pull out the pieces that are of interest. Still other approaches deal with developing "ontologies", or hierarchical vocabularies intended to represent the content domain.

There are a number of companies (including our own) that offer commercial applications specifically intended to do screen-scraping. The applications vary quite a bit, but for medium to large-sized projects they're often a good solution. Each one will have its own learning curve, so you should plan on taking time to learn the ins and outs of a new application. Especially if you plan on doing a fair amount of screen-scraping it's probably a good idea to at least shop around for a screen-scraping application, as it will likely save you time and money in the long run.

So what's the best approach to data extraction? It really depends on what your needs are, and what resources you have at your disposal. Here are some of the pros and cons of the various approaches, as well as suggestions on when you might use each one:

Raw regular expressions and code

Advantages:

- If you're already familiar with regular expressions and at least one programming language, this can be a quick solution.
- Regular expressions allow for a fair amount of "fuzziness" in the matching such that minor changes to the content won't break them.
- You likely don't need to learn any new languages or tools (again, assuming you're already familiar with regular expressions and a programming language).
- Regular expressions are supported in almost all modern programming languages. Heck, even VBScript has a regular expression engine. It's also nice because the various regular expression implementations don't vary too significantly in their syntax.

Ontologies and artificial intelligence

Advantages:

- You create it once and it can more or less extract the data from any page within the content domain you're targeting.
- The data model is generally built in. For example, if you're extracting data about cars from web sites the extraction engine already knows what the make, model, and price are, so it can easily map them to existing data structures (e.g., insert the data into the correct locations in your database).
- There is relatively little long-term maintenance required. As web sites change you likely will need to do very little to your extraction engine in order to account for the changes.

Screen-scraping software

Advantages:

- Abstracts most of the complicated stuff away. You can do some pretty sophisticated things in most screen-scraping applications without knowing anything about regular expressions, HTTP, or cookies.
- Dramatically reduces the amount of time required to set up a site to be scraped. Once you learn a particular screen-scraping application the amount of time it requires to scrape sites vs. other methods is significantly lowered.
- Support from a commercial company. If you run into trouble while using a commercial screen-scraping application, chances are there are support forums and help lines where you can get assistance.

Source:http://ezinearticles.com/?Three-Common-Methods-For-Web-Data-Extraction&id=165416

Data Extraction Product vs Web Scraping Service which is best?

Product v/s Service: Which one is the real deal?

With analytics and especially market analytics gaining importance through the years, premier institutions in India have started offering market analytics as a certified course. Quite obviously, the global business market has a huge appetite for information analytics and big data.

While there may be a plethora of agents offering data extraction and management services, the industry is struggling to go beyond superficial and generic data-dump creation services. Enterprises today need more intelligent and insightful information.

The main concern with product-based models would be their incapability to extract and generate flexible and customizable data in terms of format. This shortcoming can be majorly attributed to the almost-mechanical process of the product- it works only within the limits and scope of the algorithm.

To place things into perspective, imagine you run an apparel enterprise. You receive two kinds of data files. One contains data about everything related to fashion- fashion magazines, famous fashion models, make-up brand searches, apparel brands trending and so on. On the other hand, the data is well segregated into trending apparel searches, apparel competitor strategies, fashion statements and so on. Which one would you prefer? Obviously, the second one- this is more relevant to you and will actually make life easier while drawing insights and taking strategic calls.


In the scenario where an enterprise wishes to cut down on overhead expenses and resources to clean the data and process it into meaningful information, that’s when the heads turn towards service-based web extraction. The service-based model of web extraction has customization and ready-to-consume data as its key distinction feature.

Web extraction, in process parlance is a service that dives deep into the world of internet and fishes out the most relevant data and activities. Imagine a junkyard being thoroughly excavated and carefully scraped to find you the exact nuts, bolts and spares you need to build the best mechanical project. This is metaphorically what web extraction offers as a service.

The entire excavation process is objective and algorithmically driven. The process is carried out with a final motive of extracting meaningful data and processing it into insightful information. Though the algorithmic process leads to a major drawback of duplication, unlike a web extractor (product), wweb extraction as a service entails a de-duplication process to ensure that you are not loaded with redundant and junk data.

Of the most crucial factors, successive crawling is often ignored. Successive crawling refers to crawling certain web pages repetitively to fetch data. What makes this such a big deal? Unwelcomed successive crawling can lead to attracting the wrath of the site owners and the high probability of being sued for a class action suit.

While this is a very crucial concern with web scraping products , web extraction as a service takes care of all the internet ethics and code of conduct while respecting the politeness policies of web pages and permissible penetration depth limits.

Botscraper ensures that if a process is to be done, it might as well be done in a very legal and ethical manner. Botscraper uses world class technology to ensure that all web extraction processes are conducted with maximum efficacy while playing by the rules.

An important feature of the service model of web extraction is its capability to deal with complex site structures and focused extraction from multiple platforms. Web scraping as a service requires adhering to various fine-tuning processes. This is exactly what botscraper offers along with a highly competitive price structure and a high class of data quality.

While many product-based models tend to overlook the legal aspects of web extraction, data extraction from the web as a service covers it much more ingeniously. While associating with botscraper as web scraping service provider, legal problems should be the least of your worries.

Botscraper as a company and technology ensures that all politeness protocol, penetration limits, robots.txt and even the informal code of ethics is considered while extracting the most relevant data with high efficiency.  Plagiarism and copyright concerns are dealt with utmost care and diligence at Botscraper.

The key takeaway would be that, product-based web extraction models may look appealing from a cost perspective- that too only at the face of it, but web extraction as a service is what will fetch maximum value to your analytical needs. Ranging right from flexibility, customization to legal coverage, web extraction services score above web extraction product and among the web extraction service provider fraternity, botscraper is definitely the preferred choice.


Source: http://www.botscraper.com/blog/Data-Extraction-Product-vs-Web-Scraping-Service-which-is-best-

Introduction About Data Extraction Services

Introduction About Data Extraction Services

World Wide Web and search engine development and data at hand and ever-growing pile of information have led to abundant. Now this information for research and analysis has become a popular and important resource.

According to an investigation "now a days, companies are looking forward to the large number of digital documents, scanned documents to help them convert scanned paper documents.

Today, web services research is becoming more and more complex. The business intelligence and web dialogue to achieve the desired result if the various factors involved. You get all the company successfully for scanning ability and flexibility to your business needs to reach can not scan documents. Before you choose wisely you should hire them for scanning services.

Researchers Web search (keyword) engine or browsing data using specific Web resources can get. However, these methods are not effective. Keyword search provides a great deal of irrelevant data. Since each web page has many outbound links to browse because it is difficult to retrieve the data.

Web mining, web content mining, the use of web structure mining and Web mining is classified. Mining content search and retrieval of information from the web is focused on. Mining use of the extract and analyzes user behavior. Structure mining refers to the structure of hyperlinks.

Processing of data is much more financial institutions, universities, businesses, hospitals, oil and transportation companies and pharmaceutical organizations for the bulk of the publication is useful. There are different types of data processing services are available in the market. , Image processing, form processing, check processing, some of them are interviewed.

Web Services mining can be divided into three subtasks:

Information(IR) clearance: The purpose of this subtask to automatically find all relevant information and filter out irrelevant. Google, Yahoo, MSN, etc. and other resources needed to find information using various search engines like.

Generalization: The purpose of this subtask interested users to explore clustering and association rules, including using data mining methods. Since dynamic Web data are incorrect, it is difficult for traditional data mining techniques are applied to raw data.

Data (DV) Control: The former works with data that knowledge is trying to uncover. Researchers tested several models they can emulate and eventually Internet information is valid for stability.

Source:http://www.sooperarticles.com/business-articles/outsourcing-articles/introduction-about-data-extraction-services-500494.html

New technology Of Website Data Scraping

New technology Of Website Data Scraping

Proved to scrape data from websites using the software program is the process of extracting data from the Web. We offer the best web software to extract data. That kind of experience and knowledge in web data extraction is completed image, screen scrapping, email extractor services, data mining, web hoarding.

You can use the data scraping services?

Data as the information is available on the network, name, word, or what is available in web. be removed, restaurants our city California software and marketing company to use the data from these data can market their product as restaurants. Vast network construction and large building group for your product and company.

Web Data Extraction

Websites tagged text-based languages (HTML and XHTML) are created using, and often contain a lot of useful data as text. However, the majority of web pages and automate human end users are not designed for ease of use. Because of this, scrape toolkits that web content is created. A web scraper to have an API to extract data from a Web site. We have a variety of APIs that you need to scrape data helps help. We offer quality and affordable web applications for data mining

Data collection

In general; the information of the data transfer between the programs, people automatically by computer processing is performed by appropriate structures. Such formats and protocols are strictly structured change documented, analyzed easily, and to maintain a minimum ambiguity. Often, these transmissions are not readable.

Email Extractor

A tool that automatically any reliable source called an email extractor to extract email ids help. It is fundamentally different websites, HTML files, text files or any other format without ID duplicate email contacts collection services.

Screen Scrapping

Data mining is the process of extracting patterns from data services. Data mining to transform data into information is becoming an increasingly important tool. MS Excel, CSV, HTML and many other formats, including any format according to your needs.

Spider Web

A spider is a computer program that a methodical, automated or in an orderly way to surf the World Wide Web. Many sites, in particular search engines, providing up-to-date data, use speeding as a means. There are literally thousands of free proxy servers located throughout the world that are very easy to use.
Web Grabber

Web Grabber is just another name for data scraping or data extraction. Different techniques and processes designed to collect and analyze data, and has developed over time. Web Scraping for business processes that have beaten the market recently is one. It is a process from various sources such as websites and databases with large amounts of data provides.
Have you ever heard "data scraping?" Scraping data scraping technology to new technologies and a successful businessman made his fortune by taking advantage of the data is not.

Source: http://www.selfgrowth.com/articles/new-technology-of-website-data-scraping

Web Data Extraction Services and Data Collection Form Website Pages

Web Data Extraction Services and Data Collection Form Website Pages

For any business market research and surveys plays crucial role in strategic decision making. Web scrapping and data extraction techniques help you find relevant information and data for your business or personal use. Most of the time professionals manually copy-paste data from web pages or download a whole website resulting in waste of time and efforts.

Instead, consider using web scraping techniques that crawls through thousands of website pages to extract specific information and simultaneously save this information into a database, CSV file, XML file or any other custom format for future reference.

Examples of web data extraction process include:
• Spider a government portal, extracting names of citizens for a survey
• Crawl competitor websites for product pricing and feature data
• Use web scraping to download images from a stock photography site for website design

Automated Data Collection
Web scraping also allows you to monitor website data changes over stipulated period and collect these data on a scheduled basis automatically. Automated data collection helps you discover market trends, determine user behavior and predict how data will change in near future.

Examples of automated data collection include:
• Monitor price information for select stocks on hourly basis
• Collect mortgage rates from various financial firms on daily basis
• Check whether reports on constant basis as and when required

Using web data extraction services you can mine any data related to your business objective, download them into a spreadsheet so that they can be analyzed and compared with ease.

In this way you get accurate and quicker results saving hundreds of man-hours and money!

With web data extraction services you can easily fetch product pricing information, sales leads, mailing database, competitors data, profile data and many more on a consistent basis.

Source:http://ezinearticles.com/?Web-Data-Extraction-Services-and-Data-Collection-Form-Website-Pages&id=4860417

Understanding URL scraping

Understanding URL scraping

URL scraping is the process where you automatically extract and filter URLs of WebPages that have specific features. The features that you are looking for vary depending on your goal. For example, if you are looking for a site where you can place your comment and get back link juice, you should go for WebPages that allow dofollow comments.

Techniques for URL scraping

There are many techniques that you can use to get the URL that you are looking for. Some of these techniques include:

Copy pasting: this is where you visit a given site and check whether it has the features that you are looking for. For example, if you are interested in dofollow links, you should visit a number of sites and find out if they have your target links. You should then identify the ones that have the features that you are looking for and compile a list.

Text grepping: this is a technique that allows you to search plain text on websites that match a regular expression. Although, the technique was designed for Unix, you can also use it on other operating systems.

HTTP programming: here you retrieve the WebPages that have the features that you are looking for. You should then note the URL of the pages. To retrieve the pages you have to post HTTP requests using a remote server that uses socket programming.

HTML Parser: a HTML parser allows you to mine data by detecting a common template, script or code on a specific website or Webpage. To be able to detect the script or code you have to use one of the many programming languages: HTQL, Java, PHP, XQuery and Python. Once the data is extracted, it's translated and packaged in a way that you are able to easily understand it.

DOM parsing: This is a technique where you retrieve dynamic content that has been generated by client side scripts that execute in a web browser such as Google Chrome, Mozilla Firefox or any other browsers.

URL scraping software: this is the easiest way of scraping URLs as all you need is high quality software that will do all the work for you. You should identify the features that you are interested in and then give command to the software. The software will go through all the sites on the internet and extract the URLs of the pages that have your target features.

Source: http://www.amazines.com/article_detail.cfm/6180373?articleid=6180373

Benefits of data extraction for the healthcare system

Benefits of data extraction for the healthcare system

When people think of data extraction, they have to understand that is the process of information retrieval, which extract automatically structured information from semi-structured or unstructured web data sources. The companies that do data extraction provide for clients specific information available on different web pages. The Internet is a limitless source of information, and through this process, people from all domains can have access to useful knowledge. The same is with the healthcare system, which has to be concerned with providing patients quality services. They have to deal with poor documentation, and this has a huge impact on the way they provide services, so they have to do their best and try to obtain the needed information. If doctors confront with a lack of complete documentation in a case, they are not able to proper care the patients. The goal of data scraping in this situation is to provide accurate and sufficient information for correct billing and coding the services provided to patients.

The persons that are working in the healthcare system have to review in some situations hundred of pages long documents, for knowing how to deal with a case, and they have to be sure that the ones that contain useful information will be protected for being destroyed or lost in the future. A data mining company has the capability to automatically manage and capture the information from such documents. It helps doctors and healthcare specialists to reduce their dependency on manual data entry, and this helps them to become more efficient. If it is used a data scraping system, data is brought faster and doctors are able to make decisions more effectively. In addition, the healthcare system can collaborate with a company that is able to gather data from patients, to see how a certain type of drug reacts and what side effects it has.

Data mining companies can provide specific tools that can help specialists extract handwritten information. They are based on a character recognition technology that includes a continuously learning network that improves constantly. This assures people that they will obtain an increased level of accuracy. These tools transform the way clinics and hospitals manage and collect data. They are the key for the healthcare system to meet federal guidelines on patient privacy. When such a system is used by a hospital or clinic, it benefits from extraction, classification and management of the patient data. This classification makes the extraction process easier, because when a specialist needs information for a certain case he will have access to them in a fast and effective way. An important aspect in the healthcare system is that specialists have to be able to extract data from surveys. A data scraping company has all the tools needed for processing the information from a test or survey. The processing of this type of information is based on optical mark recognition technology and this helps at extracting the data from checkboxes more easily. The medical system has recorded an improved efficiency in providing quality services for patients since it began to use data scrapping.

Source: http://www.amazines.com/article_detail.cfm/6196290?articleid=6196290

Data Mining's Importance in Today's Corporate Industry

Data Mining's Importance in Today's Corporate Industry

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

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

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

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

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

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

It is available in various forms like text, web, audio & video data mining, pictorial data mining, relational databases, and social networks. Data mining is thus also known as Knowledge Discovery in Databases since it involves searching for implicit information in large databases. The main kinds of data mining software are: clustering and segmentation software, statistical analysis software, text analysis, mining and information retrieval software and visualization software.

Data Mining therefore has arrived on the scene at the very appropriate time, helping these enterprises to achieve a number of complex tasks that would have taken up ages but for the advent of this marvelous new technology.

Source:http://ezinearticles.com/?Data-Minings-Importance-in-Todays-Corporate-Industry&id=2057401

Data Mining Introduction

Data Mining Introduction

Introduction

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

The cause and solution to this increase in data to be processed has been because the increasing power of computer technology has increased data collection and storage. Direct hands-on data analysis has increasingly been supplemented, or even replaced entirely, by indirect, automatic data processing.

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

It can be easily be divided into stages

Pre-processing

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

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

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

Data mining

Data mining commonly involves four classes of task:

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

Validation of Results

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

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

Source : http://ezinearticles.com/?Data-Mining-Introduction&id=2731583

Data Mining - Efficient in Detecting and Solving the Fraud Cases

Data Mining - Efficient in Detecting and Solving the Fraud Cases

Data mining can be considered to be the crucial process of dragging out accurate and probably useful details from the data. This application uses analytical as well as visualization technology in order to explore and represent content in a specific format, which is easily engulfed by a layman. It is widely used in a variety of profiling exercises, such as detection of fraud, scientific discovery, surveys and marketing research. Data management has applications in various monetary sectors, health sectors, bio-informatics, social network data research, business intelligence etc. This module is mainly used by corporate personals in order to understand the behavior of customers. With its help, they can analyze the purchasing pattern of clients and can thus expand their market strategy. Various financial institutions and banking sectors use this module in order to detect the credit card fraud cases, by recognizing the process involved in false transactions. Data management is correlated to expertise and talent plays a vital role in running such kind of function. This is the reason, why it is usually referred as craft rather than science.

The main role of data mining is to provide analytical mindset into the conduct of a particular company, determining the historical data. For this, unknown external events and fretful activities are also considered. On the imperious level, it is more complicated mainly for regulatory bodies for forecasting various activities in advance and taking necessary measures in preventing illegal events in future. Overall, data management can be defined as the process of extracting motifs from data. It is mainly used to unwrap motifs in data, but more often, it is carried out on samples of the content. And if the samples are not of good representation then the data mining procedure will be ineffective. It is unable to discover designs, if they are present in the larger part of data. However, verification and validation of information can be carried out with the help of such kind of module.

Source:http://ezinearticles.com/?Data-Mining---Efficient-in-Detecting-and-Solving-the-Fraud-Cases&id=4378613

Data Mining: Its Description and Uses

Data Mining: Its Description and Uses

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

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

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

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

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

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

Generally, any of the following relationships are obtained.

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

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