Things to know about web scraping

Things to know about web scraping

First things first, it is important to understand what web scraping means and what is its purpose. Web scraping is a computer software technique through which people can extract information and content from various websites. The main purpose is to use that information in a way that the site owner does not have direct control over it. Most people use web scraping in order to turn commercial advantage of their competitors into their own.

There are many scraping tools available on the Internet, but because some people might think that web scraping goes long beyond their duties, many small companies that provide this type of services have appeared on the market. This way, you can turn this challenging and complex process into an easy web scraping one, which, believe it or not, exists for nearly as long as the web. All you have to do is some quick research on the Internet and find the best consultant that is willing to help you with this matter. When it comes to the industries that web scraping is targeting, it is worth mentioning that some of them prevail over others. One good example is digital publishers and directories. They are one of the easiest targets for web scrappers, because most of their intellectual property is available to a large number of people. Industries like travel or real estate are also a good place for scraping, along with ecommerce, which is an obvious target too. Time-limited promotions and even flash sales are the reasons why ecommerce is seen as a candy by web scrapers.

Source: http://www.amazines.com/article_detail.cfm/6196289?articleid=6196289

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

Facts on Data Mining

Facts on Data Mining

Data mining is the process of examining a data set to extract certain patterns. Companies use this process to determine the outcome of their existing goals. They summarize this information into useful methods to create revenue and/or cut costs. When search engines are accessed, they begin to build lists of links from the first page it accesses. It continues this process throughout the site until it reaches the root page. This data not only includes text, but also numbers and facts.

Data mining focuses on consumers in relation to both "internal" (price, product positioning), and "external" (competition, demographics) factors which help determine consumer price, customer satisfaction, and corporate profits. It also provides a link between separate transactions and analytical systems. Four types of relationships are sought with data mining:

o Classes - information used to increase traffic
o Clusters - grouped to determine consumer preferences or logical relationships
o Associations - used to group products normally bought together (i.e., bacon, eggs; milk, bread)
o Patterns - used to anticipate behavior trends

This process provides numerous benefits to businesses, governments, society, and especially individuals as a whole. It starts with a cleaning process which removes errors and ensures consistency. Algorithms are then used to "mine" the data to establish patterns.

 Source: http://ezinearticles.com/?Facts-on-Data-Mining&id=3640795