Scraping is one simple technique used to collect data and content from any website. It can be performed either manually or automatically. However, relatively expensive and complex software programs have to be used for autonomous data scraping.
On the other hand, mining processes and analyzing massive databases help with data cleaning and uncovering insights. You can utilize mining to enhance your sales, strengthen customer connections, and reduce risks as a retailer.
As far as the utility is concerned, each process has its own applications. Retailers and financial analysts use data mining in their respective industries. Retailers, for example, like to use mining to study the graph of their company's growth and decline to develop more profitable and effective sales methods. Likewise, finance analysts wish to employ mining to explore possible investment prospects and predict the success of their startup. Web data scraping, on the contrary, is just the extraction of content using bots. It is exclusively used in data-driven digital enterprises to convert the collected data into better forms such as excel. Legitimate use cases of scrapping include search engine bots crawling a site, rating it, and analyzing its content.
Web data scraping has nothing to do with data scanning; it is simply a method of collecting data. On the other side of the coin, there is mining, an all-embracing process of examining large collections of data to identify and uncover patterns and trends.