Data Mining: What Is It and Why Does Your Business Need It?

Data mining is a technique that can supercharge your marketing strategy — but you need to understand it well to use effectively. This article will help you.

Data Mining: What Is It and Why Does Your Business Need It?
Lucas Walker
Lucas Walker 6 min read
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With big data as one of the primary tools for success these days, businesses are increasingly trying to harness and use it for their profit. That’s why data mining became such a popular service. But what is it exactly and, well, how does data get mined? Could you ever execute this process by yourself or do you need a data scientist? This article will try to answer your questions.

What is data mining?

First things first, let’s define this term:

Data mining is the analysis of a vast amount of data with the goal to detect any patterns and nuances that could be useful for a business.

As the definition suggests, it's a complicated and time-demanding process that would be very difficult to outsource to a single human. That’s why data scientists come up with all kinds of sophisticated algorithms that can process information and sift out the useful bits much quicker and more efficiently than a human (or a group of people, for that matter) would.

The integral part of data mining is data gathering: You need to obtain massive volumes of information first to have something you could work with. The data also gets gathered by algorithms — bots called crawlers and scrapers. Crawlers simply get all the information from the destination website, while scrapers are also capable of processing said data and only getting the relevant pieces.

Various user data is being gathered

After the data is scraped, we can proceed to the mining stage. But data mining has some pitfalls we need to talk about.

Why is data mining so popular and important today?

The internet is full of information. But it’s very unstructured (also called "raw"), so working with it in its unstructured form is too complicated. Data mining allows to structure it and then use this information to:

  • Gain competitive intelligence
  • Accelerate research
  • Make data-based and correct decisions

Data mining use cases

This tool is valuable virtually for anyone. Here are some use cases that could help you get a better grasp on the importance of data mining.


Data mining is essential for academic research

Nowadays, we have access to tremendous volumes of data. In its unstructured form, however, it has almost no use for us. Data mining speeds up academic research, making it more precise and true. Educators can use this tool to predict and track the performance of their students to realize who might need some more help than others.


Structured and ready-to-use information makes targeting and other marketing processes way simpler: Marketing specialists can analyze and work with the data more effectively. Thanks to data mining, it’s easy for them to predict customer behavior and improve the efficiency of campaigns.


It’s difficult to forecast the demand precisely — but data mining makes this process way more accurate and straightforward as structured information provides manufacturers with the opportunity to analyze trends. Using this data, they can optimize the processes by aligning them with demand. Also, with the help of data mining, they can easily detect fraud, improve their positions on the market, and make sure they’re compliant with all the regulations.


Numerous apple manufacturers' data is being mined

Just like manufacturers, retailers can put structured data to use to improve their income, predict the demand, study their target audience and make the most out of marketing campaigns. It’s very simple to keep an eye on the activity of competitors, too.

Insurance companies

Using data mining, insurance agencies can manage risks, take compliance under control, and detect fraud easily. Such companies also use structured information to study their customers and gain better positions on the market.


Banking data is being used to detect frauds

Similarly to insurance companies, banks can use data mining to detect fraud, and manage risks  and compliance. They can also analyze and keep track of all those transactions that are held by their customers every day. Thus, utilizing structured information, banks can improve many of their processes.

Things to know about data scraping

It’s easy to find a scraper that would be able to do the job for you. Yet, everything is more complicated than it looks on the surface. The issue is that most website owners are not excited about their data getting gathered.

There are multiple reasons for that: for example, some might not want their rivals to get a competitive advantage this way. Others may just want to protect their websites from unscrupulous gatherers who would ignore the intellectual property or violate the rights of website owners in some other way.

❔ Further reading: How Legal Is Web Scraping — and How to Avoid Legal Problems?

Therefore, most sites are protected from data scraping. The protective measures are different — some websites feature CAPTCHAs, while others detect bot-like activity and ban the IP address from which requests are coming.

An example of reCAPTCHA

With the right technology, however, every issue can be addressed — and anti-scraping measures are not an exception. Advanced scrapers have a multitude of settings you can tweak to achieve the desired results. For example, you could make your scraper operate slower so that its behavior mimics the behavior of a real user. Also, some robots allow adding supporting tools such as optical character recognition for reading CAPTCHAs.

However, the main problem is the IP address. A scraper sends too many requests for the destination site to believe it’s a real human just browsing the pages. Therefore, to avoid getting blocked you should change IP addresses for each request. It can be done with proxies.

How to use proxies for data mining?

There are three kinds of proxies — residential, data center, and mobile. We need the first type for data gathering. Residential proxies are real devices you can connect to in order to route your traffic through a proxy gadget. By doing so, you will pick up the IP address of this device and cover your real one with it.

Then once you access the destination website, its servers will see the IP of a proxy, not your real one. And since residential proxies are real devices, you will appear as a resident of a certain location to a destination website — not as a person who is using proxies.

So if you apply a number of residential proxies to your scraper and set it up so that the bot changes IPs with every request, you can expect the data gathering to be smooth. The only thing to watch out for in this situation is the quality of proxies.

You can find free residential proxies, but we advise against using them. It’s not easy to manage the network of proxies, let alone obtaining residential IPs. So you can’t expect such a complex service to be free and high-quality. Quite likely, once you get those free proxies, you will see that most of them are blocked already.

Infatica offers affordable residential proxies that won’t be a burden for your budget. You can choose the number of IPs and locations you need — our pricing plans are flexible enough to fit any needs. And if you feel like none of the options we offer truly meet your requirements, just contact us so that we create a custom pricing plan for you. Easy as that! Our proxies are always ready to work with as we expand the pool of IPs constantly and replace blocked ones quickly.

Frequently Asked Questions

Data mining is the analysis of a vast amount of data with the goal to detect any patterns and nuances that could be useful for a business. Data mining types include predictive and descriptive.

Predictive data mining typically includes classification analysis, regression analysis, time serious analysis, and prediction analysis.

Descriptive data mining typically includes clustering analysis, summarization analysis, association rules analysis, and sequence discovery analysis.

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