Often people who deal with data on a regular basis use both the terms – web scraping and data mining simultaneously. But have you wondered that both are quite different from each other?
Yes, you heard it right! Web Scraping and Data Mining might share some similarities with each other, but they are fundamentally different from each other.
Although they both are linked to extracting value from something valuable only when processed, they have distinct applications.
If you are also not sure about the true meaning of both terms, don’t worry we have got your back. In this article, we have mentioned everything that you need to understand about them both.
Both concepts are gaining huge popularity in recent times of advancement in technology because of their widespread usage in data-related functions. But let’s start with their respective definitions to gain an in-depth understanding of their meaning.
What is Web Scraping?
Web Scraping Definition can be best explained as a method of collecting and extracting data from required web pages to further use in crucial business operations. There are multiple web scraping tools and APIs that gather valuable data as per your needs. The information is then saved in a central database and can be extracted directly from the websites.
It eliminates all the barriers of scraping the information from official sources only and provides you access to all publicly available data on online platforms.
Read More: Web Scraping Explained Thoroughly.
What is Data Mining?
Data Mining Definition can be the act of deriving crucial information from the raw data by analyzing it for trends and current needs. Generally, data is sourced through a variety of pages and methods like Google Forms surveys, public records, data scraping, and much more.
But to make the maximum usage of this data and generate results that are beneficial for a particular type of business, data mining plays an essential role. It helps in deducing the key insights of the data to create and bring something meaningful out of it.
Check out these 20 data mining software too!!
Differences in Applications of Data Mining & Web Scraping
Another key difference between the two terms can be explained through their usage and difference in applications.
Web Scraping applications are often centric in operations where a continuous stream of data is required. For example, marketing campaigns often require a high amount of data to ethically use as leads or base of the campaign.
Similarly, pricing is another area that many businesses extract to conduct market analysis, competitive analysis, and in other product development functions.
Another usage and benefit of web scraping are in the area of live weather forecasting. By scraping real-time information through different sources, one can easily provide accurate and live data to their customers.
Read More: Use Cases of Web Scraping that Almost Every Business Can Implement
On the other hand, Data Mining applications are purposed to create value from the existing data. Often, the data science industry requires data mining software for its projects and day-to-day operations.
Apart from that, most businesses use data mining for their business strategy planning, predictions, and marketing functions. Since it provides meaningful insights from the existing data, it becomes easier for industry experts to further optimize their functions in a manner to deduce results.
What is the Connection Between Web Scraping and Data Mining?
Apart from the fact that both are different from each other, they hold a strong connection with each other that helps business owners leverage their business operations. Web scraping can create rich data sources and helps in the extraction of crucial data from different sites.
This data is then further analyzed and assessed with the help of data mining to deduce meaningful results from the same. In this manner, web scraping enables data mining and helps businesses to boost their performance.
For example, Scraping prices can help in the collection of commercial data like product range, features, ratings, reviews, stock status, and much more. This information is then analyzed with the help of data mining to generate powerful business insights and accordingly plan one’s own strategy.
Similarly, you can scrape off a huge amount of data posted on different social media platforms like keywords, hashtags, reviews, and much more. This enables data mining to reveal detailed information about the competitors, customer perspective, positive or negative brand image, and other insights that can help you boost your efficiency.
The Moment of Truth
We hope that you now might be able to distinguish between data mining and data scraping. But, it’s time for the moment of truth and to summarize the difference between the two terms.
So, Web scraping is the process of extracting data from web sources and structuring it into a more convenient or usable format. It is a direct process of data collection without involving any further processing or analysis.
While on the other hand, Data mining is the process of analyzing large datasets to deduce and provide valuable insights, patterns, and trends. It does not involve the collection of data like web or data scraping.
Web scraping could be used to create huge datasets and data mining could be used to analyze them for in-depth insights.
Conclusion
We hope that our article helped you understand that Web Scraping and Data Mining aren’t synonymous with each other. Rather, the confusion is the result of their relatable applications and uses.
Mostly, since both are used together to serve a greater purpose, people often end up using them interchangeably. In the emerging era of technology like today, businesses rely heavily on data and its interpretation to perform most of their functions.
Thus, it is better advised to use both data scraping and data mining tools in your operations. This will help you in getting access to the ever-changing market demands and needs of your customers. So, get started today.
Additional Resources
Web Scraping with Scrapingdog
