Back to Blog

What is the Difference Between Data Mining and Web Scraping?

Understand the distinction between data mining and web scraping. These are the two words that are frequently used interchangeably.


Catagory
Services
Publish Date
Aug 16, 2022
Author
Scraping Intelligence
What-is-the-Difference-Between-Data-Mining-and-Web-Scraping
Table Of Content

    There is often confusion between data mining and website data extraction, although they are two entirely different processes. There is a common misconception that data mining is acquiring information from websites.

    In today's blog, we will define web scraping, explain its applications, and discuss the projects you'll encounter as a data analyst.

    Defining Data Mining

    Data mining aims to explore business intelligence which will assist organizations in resolving issues, reducing risks, and exploring new possibilities. Mining for rare metals, precious stones, and minerals is analogous to sifting through massive databases for helpful information in this area of data science. It requires enormous quantities of raw materials to uncover hidden value in both procedures.

    Using data mining, resolving business problems becomes easy because manual solutions would take too long. Users can spot patterns, trends, and relationships that they might otherwise overlook by using powerful computers and algorithms to execute various statistical procedures that analyze data in multiple ways.

    Sales and marketing, healthcare, product development, and education are some of the areas that use data mining. As a result of data mining, you will be able to better understand your customers, develop effective marketing policies, revenue increase, and decrease costs.

    Working on Data Mining

    Most data scientists have a process they use when trying to address a business problem. It can help you focus your efforts by providing a clear structure, even though there is no right or wrong method to undertake data mining.

    You can divide the process into four steps:

    We are defining the business problem

    At this point, the data science team and the business stakeholders want to describe the problem they're trying to solve and provide a hypothesis about how data can do so.

    Cleaning and Organizing the Data

    Data analysts and scientists can now begin gathering and cleaning the data sets they will use for the project with a clear understanding of the issues and the research's parameters. They will need to collect the data through web scraping, APIs, and any other source necessary if they don't already have it to inform the identified issue.

    Model Construction and Data Mining

    Here, data analysts will employ strategies like association rules, decision trees, KNN, and machine learning algorithms to draw patterns, anomalies, and trends from the gathered data.

    Implementation and evaluation of knowledge

    The final step to influencing choices, exploiting hidden opportunities, or addressing concerns is to ensure the data is valid, novel, helpful, and understandable by analyzing it.

    Is Data Mining Process Legal?

    The sources of the raw data utilized in data mining are as varied as the applications for data mining. There are many applications for forecasting consumer behavior in the financial sector, in science, engineering, agriculture, and crime prevention.

    Data mining, or the process of extracting useful information from big public data sets, is not always wrong. From a legal and ethical perspective, how the information was obtained and used may be in doubt.

    The general public has access to facts regarding moving traffic or weather prediction. But it's essential to be aware of legal limitations like copyright and data privacy laws.

    Defining Web Scraping

    The act of directly obtaining data from web pages is known as web scraping. Target website, web scraping technology and database to store collected data are typically the three basic needs for web scraping.

    You are not constrained to official data sources using web scraping. You can instead utilize all publicly accessible data on websites and other internet channels. In actuality, web scraping occurs when you merely visit a website and manually write down its data. However, manual site scraping is highly time and energy-consuming. Not to add that most publicly accessible data are rarely present on a website's front end.

    What Is the Purpose of Web Scraping?

    Web data extraction is frequently recycled or used in real-time applications that need a constant stream of data. Contact information can be utilized responsibly as leads in marketing initiatives with the proper approvals.

    The same applies to prices. If you were to develop an app that compares the costs of particular goods or services, you could offer a live comparison of pricing from other websites. Web scraping makes price comparison easy.

    Weather data is the most popular live web scraping application. Most weather applications don't gather their weather information on Windows, Android, and Apple devices. Instead, they include accurate data into their unique app UI that they import from reliable weather forecast suppliers.

    Comparing Data Mining and Web Scraping

    This point should make it quite obvious how those two words differ. But let's state it more plainly. Web scraping is gathering and organizing data from online sources in a more usable way. There is no data processing or review involved.

    Data extraction is not the goal of data mining. Data mining is the process of examining massive data sets to find patterns and relevant information. It doesn't need to process or extract data. It is possible to mine data from the web by scraping it.

    Conclusion

    Data mining and web scraping are not interchangeable and have pretty different meanings. However, it doesn't follow that you always have to favor one over the other.

    Web scraping is the only reliable method of gathering data for mining. Additionally, data mining can extract more value from previously scraped information that has already served its purpose.

    With the aid of automated technologies, you can extract the data you require on your own, or you can pay a business-like Scraping Intelligence to do it for you.


    About the author


    Zoltan Bettenbuk

    Zoltan Bettenbuk is the CTO of ScraperAPI - helping thousands of companies get access to the data they need. He’s a well-known expert in data processing and web scraping. With more than 15 years of experience in software development, product management, and leadership, Zoltan frequently publishes his insights on our blog as well as on Twitter and LinkedIn.

    Latest Blog

    Explore our latest content pieces for every industry and audience seeking information about data scraping and advanced tools.

    web-scraping-using-python-a-step-by-step-tutorial-guide-2025
    Services
    08 July 2025
    Web Scraping Using Python: A Step-By-Step Tutorial Guide (2025)

    No matter what industry you belong to, web scraping helps extract insights from industry datasets. It is a systematic process of getting data from online sources, top-ranking websites, popular platforms, and databases.

    guide-to-alcohol-data-scraping-pricing-trends-and-legal-risks
    Services
    24 Jun 2025
    The Ultimate Guide to Alcohol Data Scraping: Pricing, Trends & Legal Risks

    Learn how to scrape alcohol pricing & market trends safely. Explore legal risks, best tools, and strategies for extracting beverage industry data efficiently.

    The Complete Guide to Web Scraping
    Google
    19 Jun 2025
    How to Scrape Google Shopping for Price and Product Data?

    Learn how to collect real-time data from Google Shopping, which has an array of products and simple steps to scrape price and product data from Google Shopping.