In very simple words data mining involves collecting, processing, storing and analysing data in order to discover (and extract) new information from it.
Data mining methods range from extremely complicated to basic. Each strategy provides a little bit different purpose or objective. Essentially, data mining helps companies evaluate amazing amounts of information to be able to identify common styles or learn new things. It would be impossible to process all this information without automated. Here are a few example techniques to information mining:
Cluster identification is a type of design identification that is used to identify styles within huge information places. It’s a bit like organising a lot of information into groups using styles which appear during information research (and might not be very obvious).
Anomaly identification is designed to find irregularities in information. This can be used in many areas, such as discovering flaws in weather styles or even forensic processing.
Regression is a strategy that is designed to estimate upcoming results using huge places of current factors. This is used to estimate upcoming user involvement, client preservation and even property prices.
There are many other techniques to information exploration. Ultimately, the strategy that you choose is determined by your end objective and there is no individual strategy that includes every subject out there.
There are below key benefits of Data Mining.
1. 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.
2. In marketing, data mining techniques are used to improve conversions, increase customer satisfaction and created targeted advertising campaigns. They can even be utilised when analysing 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.
3. Retail stores use customer shopping habits/details to optimise the layout of their stores in order to improve customer experience and increase profits.
4. Tax governing bodies use data mining techniques to detect fraudulent transactions and single out suspicious tax returns or other business documents.
5. In manufacturing, data discovery is used to improve product safety, usability and comfort.
GrassDew has four main business streams – Consulting Services, Software Solutions, Security Services and Knowledge Services. Our primary focus is on various software development and maintenance services.
To know more about our services, email us at shekhar.pawar@grassdew.com