Web Scraping vs. Data Mining: What You Need to Know

To understand the differences between web scraping vs. data mining, and why they’re both important, start by considering the value of data.

Data has emerged as the essential connection to uncover trends or buying behavior between customers and businesses. A potent source of valuable insights, data is the driving force behind web scraping and data mining methodologies.

But how do we go about collecting it?

That’s where web scraping and data mining come in. Although the two are often mentioned together, they do not have the same objectives. They do have some similarities, which is where the confusion begins.

Let’s define each term and help you understand their differences more clearly.

What is Web Scraping?

Web scraping is a form of extraction in which valuable data is collected from various web sources. It requires two components: a crawler and a scraper.

How Does Web Scraping Work?

Web scraping can be done manually or by using scrapping tools and applications that can read programming languages such as CSS, JavaScript, and HTML. Using the Hypertext Transfer Protocol, these tools access world wide web pages and scrape entire articles to collect written data or multimedia images. At this stage, the extracted information is just raw data that can be replicated, automated to meet specific criteria, further programmed, or presented in cohesive formats such as spreadsheets.

Where Do We Use Web Scraping?

Corporations regularly adopt web scraping tools to collect service information to understand consumer behavior better. Some specific web scraping use cases are:

  • Pricing Intelligence: Collect purchasing information from prospective customers to ensure the best prices are set, and sale opportunities aren’t missed.
  • Understanding Rivals: Gather data about competitors’ prices, products, engagement, and marketing strategies.
  • Manage Your Reputation: Use data scraping in social media forums to keep up with your brand reputation so you know any negative discourse before it becomes problematic.
  • Sentiment Analysis: Monitor customer review forums and collect negative or positive words to analyze the reception of a new product or strategy.
  • Propel Profits: Creating leads online for your business is imperative. Use search engine result scraping to increase organic traffic to your site by maximizing SEO usage.
  • Artificial Intelligence: Perhaps the hottest topic right now, collecting data for machine learning in AI has become one of the practical uses of web scraping.

When Do We Use Web Scraping?

In the increasingly competitive corporate world, businesses seek reliable and accurate information to make data-driven decisions that drive company growth and success. Manually going through search engines for data gathering is exhausting and lengthy. This is where web scraping tools come in. Businesses and individuals use web scraping to automate data collection and efficiently gather information to fuel successful decision-making.

What is Data Mining?

Web data extraction through scraping gives us the raw data sets. Data mining is the next step. Simply put, data mining refers to the process of advanced analysis of extensive data sets. It is a fast and efficient way of analyzing large data sets to make predictions and get actionable insights.

How Does Data Mining Work?

Data mining is a structured data processing and data analysis approach that corporations frequently adopt. Data analysts use coding languages, such as Python or R, to analyze all the relevant data points extracted from the existing websites that were scraped. Data is integrated from rich data sources, and the transformed text data is presented in a more convenient format, making it easier to evaluate and interpret.

Since data mining applications extract anomalies, patterns, and trends, the results are ever-changing. As such, the most critical aspect of data mining, and data science in general, is to credit all sources and keep an updated database for storing information.

Data mining uses public information with verified approval from the owner. Data mining companies should be wary of using mined data for discriminatory research encompassing age, gender, sex, religion, or ethnicity, as it interferes with ethical mining.

Where Do We Use Data Mining?

Data mining involves analyzing large data sets to help companies identify the crux of their revenue gap. Its main aim is to create value from different data types to facilitate profit sustainability. Some cases are:

  • Revenue Increment: By identifying emerging industry trends and finding the areas of stagnation within operations, data mining helps to allocate resources to where they are needed, which boosts company revenue and decreases overhead costs.
  • Student Success: Educational institutions use data mining to predict student and teacher performance.
  • Commercial Data: Analyzing product reviews, top search engine results, and social media posts help to personalize service information and win over customer loyalty.
  • Eradicate Fraud: Data mining can be a powerful ally in detecting discrepancies and anomalies in data sets.

When Do We Use Data Mining?

Data mining is associated with data science projects and business intelligence. It helps understand the market and consumer behavior to improve online marketing strategies. It achieves actionable insights to curate marketing campaigns via strategic planning and generates predictable weekly, monthly, or annual forecasts with on-hand data.

Web Scraping vs. Data Mining

Data mining can only be done with web scraping providing a data supply. As such, web scraping is a valuable asset to data mining. Web scraping is the process that goes through all the websites to gather data that is then analyzed and presented by data mining. Web scraping collects, extracts, and discovers information, and data mining turns this information into something of value.

How Can Online Success Genie Help?

Online Success Genie is a free automated web scraping Chrome extension that is easy to install. In just one click, web scraping can be carried out precisely to save time, money, and energy to gather reliable and relevant data.

Here are three essential benefits of Online Success Genie’s web scraping system:

  • Easy Transfer of Data to MS Excel or Google Spreadsheets

Simple to use and modify, its key advantage is being transferable to Microsoft Excel or Google Spreadsheets, making acquiring key data from targeted sites a breeze. You can format and clean your data as you please before sending it over to a stakeholder.

  • Column Customization

Are you a stickler for organization and order? This added feature allows you to sort, clean, and manage your data effectively the moment you pull it out of the database. Increase or eliminate your desired columns according to your preference. Plus, you can control the data displayed to suit your business needs.

  • One Click Automation

A one-click-fits-all solution, manage your data with ease and precision to ensure that your valuable information is processed with efficacy. From removing unwanted roles to duplicating entries, you can explore the range of functions within the extension. All done in a single click, making web-scraping a walk in the park.

Final Thoughts

Web scraping and data mining are disparate processes that work hand-in-hand to help businesses gain profitable growth and expansion. As a potent monetization tool, both techniques should be a staple for any corporation.

Achieve your company’s revenue goals with relevant and reliable data to expand and keep up with current times.

Want to save even more time and money? Check out our Business Tools to do more, earn more, and save more with Online Success Genie.