The Great Advantages of Data Extraction Software – Why a Company Needs it?

Data extraction is being a huge problem for large corporate companies and businesses, which needs to be handled technically and safely. There are many different approaches used for data extraction from web and various tools have designed to solve certain problems.

Moreover, algorithms and advanced techniques were also developed for data extraction. In this array, the Data Extraction Software is widely used to extract information from web as designed.

Data Extraction Software:
 This is a program specifically designed to collect and organize the information or data from the website or webpage and reformat them.

Uses of Data Extraction Software:

Data extraction software can be used at various levels including social web and enterprise levels.

Enterprise Level: Data extraction techniques at the enterprise level are used as the prime tool to perform analysis of the data in business process re-engineering, business system and in competitive intelligence system.

Social Web Level: This type of web data extraction techniques is widely used for gathering structured data in large amount that are continuously generated by Web.2.0, online social network users and social media. 

To specify other uses of Data Extraction software:

•     It helps in assembling stats for the business plans
•     It helps to gather data from public or government agencies
•     It helps to collect data for legal needs

Does the Data Extraction Software make Your Job Simple?

The usage of data extraction software has been widely appreciated by many large corporate companies. In this array, here are a few points to favor the usage of the software;

•     Data toolbar consists of web scraping tool to automate the process of web data extraction
•     Point data fields from which the data need to be collected and the tool will do the rest
•     There are no technical skills required to use data tool
•     It is possible to extract a huge number of data records in just a few seconds

Benefits of Data Extraction Software:

This data extraction software benefits many computer users. Here follows a few remarkable benefits of the software;

•     It can extract detailed data like description, name, price, image and more as defined from a website
•     It is possible to create projects in the extractor and extract required information automatically from the site without the user’s interference
•     The process saves huge effort and time
•     It makes extracting data from several websites easy like online auctions, online stores, real estate portal, business directories, shopping portals and more
•     It makes it possible to export extracted data to various formats like Microsoft Excel, HTML, SQL, XML, Microsoft Access, MySQL and more
•     This will allow processing and analyzing data in any custom format

Who majorly Benefits from Data Extraction Software?

Any computer user benefit from this data extraction software, however, it is majorly benefiting users like;

•     Business men to collect market figures, real estate data and product pricing data
•     Book lovers to extract information about titles, authors, images, descriptions prices and more
•     Collectors and hobbyists to extract auction and betting information
•     Journalists to extract article and news from new websites
•     Travelers to extract information about holiday places, vacations, prices, images and more
•     Job seekers to extract information about jobs available, employers and more

Websitedatascraping.com is enough capable to web data scraping, website data scraping, web scraping services, website scraping services, data scraping services, product information scraping and yellowpages data scraping.

Professional Web Scraping Process

Web scraping is usually regarded as data mining and knowledge discovery. It is the process of extracting useful data and relationships from any data sources. For instance the web pages, databases and search engines. It employs pattern matching and statistical techniques. It is important to note that web scraping does not borrow from other fields like machine learning, databases, data visualization and others but supports such fields.

Web scraping process is such a complex process that requires not only time but also people with expertise in the same field. This is because the internet is such a dynamic resource that changes every time. For instance the data you can extract from a certain website a month ago will not be the same one you will extract now. The changing of data in short period of time poses the difficult of relying to such data and therefore calls for web scraping process. The web scraping process should be performed regularly in order to obtain accurate data that can be relied upon.

It is important to understand that many areas of business, science and other environments use a large amount of data. This data needs to be meaningful and knowledge in its application. Web scraping sometimes may be overlooked, but in essence it can provide very useful information than the statistical methods can produce. The web scraping methods are vital as they give you more control over the data.

Usually the data found on the internet is noisy data. This implies of the advertisements and pop-ups. The data also found on the internet can be described as dynamic data, sparse data, static data, heterogeneity and so and so forth. Such problems occur in very large amounts and therefore call for web scraping professional companies to perform their job. With such problems it is important to realize that statistical methods would never succeed and therefore calls for web scraping.

Process of web scraping

1. Identification of data sources and selection of target data. You need not to harvest any kind of data, but data that is deemed relevant and useful in its application. The relevance can be seen in a way of getting the data that will benefit your company. This is an important step in the web scraping process.

2. Pre-process.This involves cleaning and attributes selection of data before it is being harvested. Web scraping is usually done on specific websites that are relevant to your business. For instance if you have an online store and need information about your competitors products then you need data from other websites that are relevant such e-commerce stores and so on.

3. Web scraping. This involves data mining so as to extract models and information patterns or models that is beneficial to your business.

4. Post-process. After web scraping is done, it is important to identify the useful data that can be used in your business in decision making and so on.

It is important to note that the patterns identified need to be novel, understandable, potentially viable and valid for web scraping process to make sense in business data harvesting.

Source:http://www.loginworks.com/blogs/web-scraping-blogs/professional-web-scraping-process/

6 Benefits Associated with Data Mining

Data has been used from time immemorial by various companies to manage their operations.Data is needed by various organizations strategically aimed at expanding their business operations, reduction of costs, improve their marketing force and above all improve profitability. Data mining is aimed at the creation of information assets and uses them to leverage their objectives.

In this article, we discuss some of the common questions asked about the data mining technology. Some of the questions we have addressed include:

•    How can we define data mining?
•    How can data mining affect my organization?
•    How can my business get started with data mining?

Data Mining Defined

Data mining can be regarded as a new concept in the enterprise decision support system, usually abbreviated as DSS. It does more than complementing and interlocking with the DSS capabilities that may involve reporting and query. It can also be used in on-line analytical processing (OLAP), traditional statistical analysis and data visualization. The technology comes up with tables, graphs and reports of the past business history.

We may define data mining as modeling of hidden patterns and discovering data from large volumes of data.It is important to note that data mining is very different from other retrospective technologies because it involves the creation of models. By using this technology, the user can discover patterns and use them to build models without even understanding what you are after. It gives explanation why the past events happened and even predicting what is likely to happen.

Some of the information technologies that can be linked to data mining include neural networks, fuzzy logic, rule induction and genetic algorithms. In this article we do not cover those technologies but focus on how data mining can be used to meet your business needs and you can translate the solutions thereafter into dollars.

Setting Your Business Solutions and Profits

One of the common questions asked about this technology is; what role can data mining play for my organization? At the start of this article we described some of the opportunities that can be associated with the use of data. Some of those benefits include cost reduction, business expansion, sales and marketing and profitability. In the following paragraphs we look into some of the situations where companies have used data mining to their advantage.

Business Expansion

Equity Financial Limited wanted to expand their customer base and also attract new customers. They used the Loan Check offer to meet their objectives. Initiating the loan, a customer had to go to any branch of Equity branch and just cash the loan. Equity introduced a $6000 LoanCheck by just mailing the promotion to their existing customers. The equity database was able to track about 400 characteristics of every customer. The characteristics were about loan history of the customer, their active credit cards, current balance on the credit cards and if they could respond to the loan offer. Equity used data mining to shift through 400 customer features and also finding the significant ones. They used the data and build model based on the response to the Loan Check offer. They then integrated this model to 500,000 potential customers from credit bureau. They then selectively mailed the most potential customers that were determined by the data mining model.At the end of the process they were able to generate a tot
al of $2.1M in extra net income from 15,000 new customers.

Reduction of Operating Costs

Empire is one of the largest insurance companies in the country. In order to compete with other insurance companies, it has to offer quality services and at the same time reducing costs.Therefore it has to attack costs that may in form of fraud and abuse. This demands a considerable investigation skills and use of data management technology. The latter calls for data mining application that can profile every physician in their network based on claims records of every patient in their data warehouse. The application is able to detect subtle deviations on the physician behavior that are linked to her/her peer group. The deviations are then reported to the intelligence and fraud investigators as “suspicion index.” With this effort derived from data mining, the company was able to save $31M, $37M, and $41M in the first three years respectively from frauds.

Sales Effectiveness and Profitability

In this case we look into pharmaceutical sector. Their sales representatives have wide range of assortment tools they use in promoting various products to physicians. Some of the tools include product samples, clinical literature, dinner meetings, golf outings, teleconferences and many more. Therefore getting to know the promotions methods that are ideal for particular physician is of valuable importance and it is likely to cost the company a lot of dollars in sales call and thereby more lost revenue.

Through data mining, a drug maker was able to link eight months of promotional activity based on corresponding sales found in their database. They then used this information to build a predictive model for each physician.The model revealed that for the six promotional alternatives, only three had a significant impact. Then they used the knowledge found in the data mining models and thereby customizing the ROI.

Looking at those two case studies, then ask yourself, was data mining necessary?

Getting Started

All the cases presented above have revealed how data mining was used to yield results to the various businesses. Some of the results led to increased revenue and increased customer base. Others can be regarded as bottom-line improvements that impacted on cost savings and also improved productivity.In the next few paragraphs we try to answer the question; how can my company get started and start realizing the benefits of data mining.

The right time to start your data mining project is now. With the emergence of specialized data mining companies, starting the process has been simplified and the costs greatly reduced. Data mining project can offer important insights into the field and also aggregate the idea of creating a data warehouse.

In this article we have addressed some of the common questions regarding data mining, what are the benefits associated with the process and how a company can get started. Now, with this knowledge your company should start with a pilot project and then continue building a data mining capability in your company; to improve profitability, market your products more effectively, expand your business and also reduce costs.

Source: http://www.loginworks.com/blogs/web-scraping-blogs/255-benefits-associated-with-data-mining/

Why Web Scraping Software Won't Help

How to get continuous stream of data from these websites without getting stopped? Scraping logic depends upon the HTML sent out by the web server on page requests, if anything changes in the output, its most likely going to break your scraper setup.

If you are running a website which depends upon getting continuous updated data from some websites, it can be dangerous to reply on just a software.

Some of the challenges you should think:

1. Web masters keep changing their websites to be more user friendly and look better, in turn it breaks the delicate scraper data extraction logic.

2. IP address block: If you continuously keep scraping from a website from your office, your IP is going to get blocked by the "security guards" one day.

3. Websites are increasingly using better ways to send data, Ajax, client side web service calls etc. Making it increasingly harder to scrap data off from these websites. Unless you are an expert in programing, you will not be able to get the data out.

4. Think of a situation, where your newly setup website has started flourishing and suddenly the dream data feed that you used to get stops. In today's society of abundant resources, your users will switch to a service which is still serving them fresh data.

Getting over these challenges

Let experts help you, people who have been in this business for a long time and have been serving clients day in and out. They run their own servers which are there just to do one job, extract data. IP blocking is no issue for them as they can switch servers in minutes and get the scraping exercise back on track. Try this service and you will see what I mean here.

Dheeraj Juneja, Founder & CEO, Loginworks Softwares, A Virtual IT Team for your business

Loginworks Softwares Web Scraping Service

Read more about various technical stuff at our blogs: Technical Blogs

Source: http://ezinearticles.com/?Why-Web-Scraping-Software-Wont-Help&id=4550594

Basics of Web Data Mining and Challenges in Web Data Mining Process

Today World Wide Web is flooded with billions of static and dynamic web pages created with programming languages such as HTML, PHP and ASP. Web is great source of information offering a lush playground for data mining. Since the data stored on web is in various formats and are dynamic in nature, it's a significant challenge to search, process and present the unstructured information available on the web.

Complexity of a Web page far exceeds the complexity of any conventional text document. Web pages on the internet lack uniformity and standardization while traditional books and text documents are much simpler in their consistency. Further, search engines with their limited capacity can not index all the web pages which makes data mining extremely inefficient.

Moreover, Internet is a highly dynamic knowledge resource and grows at a rapid pace. Sports, News, Finance and Corporate sites update their websites on hourly or daily basis. Today Web reaches to millions of users having different profiles, interests and usage purposes. Every one of these requires good information but don't know how to retrieve relevant data efficiently and with least efforts.

It is important to note that only a small section of the web possesses really useful information. There are three usual methods that a user adopts when accessing information stored on the internet:

• Random surfing i.e. following large numbers of hyperlinks available on the web page.

• Query based search on Search Engines - use Google or Yahoo to find relevant documents (entering specific keywords queries of interest in search box)

• Deep query searches i.e. fetching searchable database from eBay.com's product search engines or Business.com's service directory, etc.

To use the web as an effective resource and knowledge discovery researchers have developed efficient data mining techniques to extract relevant data easily, smoothly and cost-effectively.

Source:http://ezinearticles.com/?Basics-of-Web-Data-Mining-and-Challenges-in-Web-Data-Mining-Process&id=4937441