Data mining using web scraping is one of the most common methods of data analysis. It simply turns raw data into meaningful information using machine learning, database systems, and statistics. Scraping forms the base of data mining because it is used to collect consumer data from different sources for further computation.
In this article, we will understand the concept of web scraping and data mining. We will also learn how you can use data mining to turn data into relevant information.
Let’s begin!
What is web scraping?
Web scraping is a data extraction technique where a web scraping software, for example this amazon product scraper, is used to extract data from websites. Scraping is particularly useful when you have to pull large amounts of data in different forms and save it for further analysis. Data is often stored in formats like excel sheets.
You can use Puppeteer for web scraping, a node library with a default headless browser, Chromium. Puppeteer offers a set of useful APIs that you can use to run your web scraping software.
Advantages of web scraping
Web scraping offers several advantages as given below:
- Automatic data extraction allows you to save ample time. You can collect large volumes of data, which otherwise would not be possible with manual data copying.
- You can extract data from websites that don’t have a public developer API.
- With your own content data sets, you can analyze your target market in-depth.
- You can scrape the SERPs to keep an eye on your competitors and achieve higher organic rankings.
- You can easily keep an eye on the pricing structure of your competitors to beat their pricing.
- By analyzing your competitors, you can quickly make intelligent and accurate business decisions.
What is data mining?
Data mining is a process to extract meaning from large sets of data. The data you gather via web scraping is processed using data mining techniques to discover meaningful patterns that aid in decision making.
Advantages of data mining
Data mining is all about turning your raw data into useful data. The different advantages of data mining are:
- Data mining models can be used to study target markets and create profitable products by predicting consumer demands. This helps to attract more customers and attention to your business.
- Data analysis is useful in predicting good or bad credit for financial organizations and banking institutions.
- Behavioral analysis allows you to understand the shopping behavior of your target audiences.
- You can stay at the forefront of all the industry trends so that you can think about your next business move.
- You can quickly offer personalized customer experiences that allow you to nurture your existing leads and retain your current customers by reducing customer churn.
Using web scraping for data mining
The first step for practical data mining is web scraping. Data mining with web scraping forms the base of useful market research and analysis.
Every business needs data to make accurate decisions. However, analyzing data is not an easy task. Here are the two steps that you need to follow to leverage web scraping for data intelligence:
Collect data using web scraping
Prepare a list of all the URLs that you wish to scrape. Inspect the page to identify the data sources. Now, prepare your code to use the data sources to automatically collect the data and send it to you in a readable format like an Excel sheet. As suggested earlier, you can use Puppeteer to make this data extraction process more manageable.
Identify the key values or fields from the collected data set.
Once you have extracted the correct information, now you have to interpret the results. This can be done by identifying the fundamental values of the data set. You need to prepare a relational database (RDBMS) and pick a primary key, a unique value for each record. You can now use the primary key values to fetch unique records from the data set necessary for further analysis. The final analysis comprises ranking the values or sorting the data using direct value comparison or group comparison.
Final Thoughts
Data mining involves a large set of data analysis using complicated mathematical functions. Data mining software is used to perform the computations. Web scraping is the most common method of feeding the data into the data mining system. Businesses should leverage the power of web scraping and data mining. It helps them to study the market and analyze the competitors to make more meaningful decisions.
