Data Mining vs. Web Scraping: What's the Difference?

Data Data Mining Web Scraping Data Analysis Data Extraction Data Science

Explore the differences between data mining and web scraping, two techniques used to extract information from various sources.

What is the difference between data mining and web scraping?

Data mining and web scraping are both techniques used to extract information from various sources, but they serve different purposes and operate in different contexts:

Key Differences Data Mining Web Scraping

Discovering patterns, correlations, or useful insights from large datasets

Automated process of extracting data from websites


To uncover hidden patterns and relationships within data that can be used to make predictions, optimize processes, or support decision-making

To gather specific data from websites for various purposes such as analysis, research, or data integration

Data Source

Structured data stored in databases, data warehouses, or other structured formats

Unstructured or semi-structured data from HTML web pages


Clustering, classification, regression, association rule mining, anomaly detection

Parsing HTML code, identifying relevant data elements, extracting data using tools or libraries

Examples of Applications

Customer segmentation, market basket analysis, fraud detection, predictive maintenance, recommendation systems

Price monitoring, content aggregation, lead generation, sentiment analysis, competitive analysis


To glean meaning from patterns of data

To format gathered data

In summary, while both data mining and web scraping involve extracting information, they serve different purposes and operate in distinct contexts. Data mining focuses on analyzing structured data to discover patterns, while web scraping extracts data from websites, primarily unstructured or semi-structured data, for various purposes.