Web Scraping and Data Mining are two terms that are often used interchangeably.
While these terms do share many similarities, they are intrinsically different.
Today, we’ll define each term and break down the differences between them.
What is Web Scraping?
Web scraping refers to the extraction of data from any website.
Generally, this also involves formatting this data into a more convenient format, such as an Excel sheet
While web scraping can be done manually, in most cases web scraping software tools are preferred due to their speed and convenience.
Want to learn more about web scraping? Check out our in-depth guide on web scraping and what it is used for.
What is Data Mining?
Data Mining refers to the process of advance analysis of extensive data sets.
These analyses can be advanced enough to require machine learning technologies in order to uncover specific trends or insights from the dataset.
For example, data mining might be used to analyze millions of transactions from a retailer such as Amazon to identify specific areas of growth and decline.
In some cases, web scraping might be used to extract and build the data sets that will be used for further analysis via Data Mining.
Web Scraping vs Data Mining: What’s the difference?
At this point, the difference between these two terms should be pretty clear. But let’s put it into simpler terms.
Web scraping refers to the process of extracting data from web sources and structuring it into a more convenient format. It does not involve any data processing or analysis.
Data mining refers to the process of analyzing large datasets to uncover trends and valuable insights. It does not involve any data gathering or extraction.
Data mining does not involve data extraction. In fact, web scraping could be used in order to create the datasets to be used in Data Mining.
The confusion between these terms most likely stems from the similarities between Data Mining and Data Extraction (which shares more similarities with Web Scraping).
If you want to learn more about Data Extraction, check out our in-depth guide on data extraction.