Data mining involves collecting, processing, storing and analyzing data in order to discover (and extract) new information from it. There are numerous benefits of data mining, but to understand them fully, you have to have some basic knowledge of what data mining actually is.
What is data mining?
Data mining techniques range from extremely complex to basic. Each technique serves a slightly different purpose or goal. In essence, data mining helps organizations analyze incredible amounts of data in order to detect common patterns or learn new things. It would be impossible to process all this data without automation. Here are a few example approaches to data mining:
- Cluster detection is a type of pattern recognition that is used to detect patterns within large data sets. It’s a bit like arranging a large amount of information into categories using patterns which emerge during data analysis (and might not be very obvious).
- Anomaly detection aims to find abnormalities in data. This can be used in many areas, such as detecting anomalies in weather patterns or even forensic computing.
- Regression is a technique that aims to predict future outcomes using large sets of existing variables. This is used to predict future user engagement, customer retention and even property prices.
There are many other approaches to data mining. Ultimately, the technique that you choose will depend on your end goal and there is no single technique that covers every topic out there.
What are the benefits of data mining?
There are many benefits of data mining. For example:
- In finance and banking, data mining is used to create accurate risk models for loans and mortgages. They are also very helpful when detecting fraudulent transactions.
- In marketing, data mining techniques are used to improve conversions, increase customer satisfaction and created targeted advertising campaigns. They can even be utilized when analyzing the needs in the market and coming up with ideas for completely new product lines. This is done by looking at historical sales and customer data and creating powerful prediction models.
- Retail stores use customer shopping habits/details to optimize the layout of their stores in order to improve customer experience and increase profits.
- Tax governing bodies use data mining techniques to detect fraudulent transactions and single out suspicious tax returns or other business documents.
- In manufacturing, data discovery is used to improve product safety, usability and comfort.
In essence, data mining benefits everyone: from individuals to large corporations and governments.