Analysis Of Different Web Data Extraction Techniques

The process of analyzing a given set of data by examining, cleaning, transforming and modeling is called as Data Analysis. To interpret and analyze rich data sources, data scientists use the techniques of data analysis to extract essential information or insights from data in different forms. It is a process of obtaining raw data and then transforming it into knowledge useful for users to make decisions. The different phases of data analysis are data collection, processing, cleaning, analysis, and modeling. A raw data can be obtained from various sources like interviews, newspapers, magazines, surveys, the Internet, etc. The Web is one of the biggest sources of obtaining static raw data which is easily available. Hence, to extract data from the oddly structured web world, web scraping techniques like web wrappers, HTTP programming, etc are used. It involves collecting data from websites or web pages and extracting data from it. This includes web crawler and data extractor. Web crawler crawls all the links present in a web page and stores them in a database whereas data extractor extracts data from these stored links. The main goal of the web scraping is to collect, store and analyze data. In this paper, we are going to study about different data extraction techniques required to collect the static data from the web for further processing and analysis.