Despite the general opinion, web page scraping is no just another term for data mining or vice versa. It is true that both processes focus on collecting and manipulating huge amounts of data from a seemingly infinite number of websites, but this is also the point where the similarity begins and ends. Furthermore the concepts are almost completely different given that web page scraping enables users to gather information while data mining allows them to analyze the information.
In this connection it might be said that the processes complement each other to a certain extent, mainly because the ultimate aim of each data extraction process is to further use the pieces of information in order to develop an accurate decision-making process. At first sight, a typical web page scraping software is built on the same premise as a data mining application, but a specialist in this field can notice the differences. The concept of screen-scraping goes back in those days when people worked on computers with green and black screens containing only text blocks. Those people used to develop a sort of screen-scraping by extracting characters from the screens so that they could be analyzed. In today’s World Wide Web, web page scraping is the advanced version of that process, which uses “spiders” or “crawlers” that browse through websites and extract pieces of data falling under certain parameters that are pre-established by the user. People employ these robots for gathering huge amounts of information from particular websites in a very short time frame, saving it into a structured format that can be filtered and analyzed. Further on, the conclusions are used for the proper development of different core processes within a company.
Putting web page scraping on a pause a bit, it’s worth noting that data mining can be described as the practice which mechanically searches huge amount of data for studies and analyzes of the functional and constructive information. In a nutshell, the user already has the information and he uses algorithms in order to identify hidden patterns, correlations, consumer trends, market trends and so on. These algorithms are very complex and based on statistical techniques which are not related with the data extraction methods employed. The algorithms are basically analyzing the information before transferring it into a functional context, which makes it easier for the end user to understand, interpret and manage the information in his behalf.
The good thing about web page scraping and data mining is that both processes can be very specific and aimed at exploiting precise and exact information. In other words, they are reliable, quick, accurate and very cost-effective, turning data studying and management into a straightforward process. The greatest aspect is that these processes provide excellent solutions for any organization, company or firm, regardless of the scale and field of activity. Web page scraping is a highly customizable operation that serves multiple purposes and interests, leading to quicker and accurate results and saving many resources in terms of money, time and effort. The variety of software applications employed for web page scraping, as well as for data mining matches the needs and requirements of any business and organization, taking core processes to a higher level and thus, making it relevant within society.