Data Mining Applications

Data mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. It is a process used to extract usable data from a larger set of any raw data. It implies analyzing data patterns in large batches of data using one or more software. It involves effective data collection and warehousing as well as computer processing. For segmenting the data and evaluating the probability of future events, It uses sophisticated mathematical algorithms. It also known as Knowledge Discovery in Data (KDD).

Actual data mining task is the semi-automatic or automatic analysis of large quantities of data to extract previously unknown, interesting patterns such as groups of data records , unusual records, and dependencies. This usually involves using database techniques such as spatial indices. These patterns can then be seen as a kind of summary of the input data, and may be used in further analysis.

Data Mining ApplicationsData mining

  • Data Mining in Finance: We have to Increase customer loyalty by collecting and analyzing customer behavior data. Also, one needs to help banks that predict customer behavior and launch relevant services and products. Helps in Discovering hidden correlations between various financial indicators that need to detect suspicious activities with a high potential risk.
  • Data Mining in Healthcare:Basically, it provides government, regulatory and competitor information that can fuel competitive advantage. Although, it supports the R&D process. And then go-to-market strategy with rapid access to information at every phase. Generally, it discovers the relationships between diseases and the effectiveness of treatments. That is to identify new drugs or to ensure that patients receive appropriate, timely care. Also, It supports healthcare insurers in detecting fraud and abuse.
  • Data mining in Telecommunication: In this, Data mining gains a competitive advantage and reduce customer churn by understanding demographic characteristics and predicting customer behavior. Increases customer loyalty and improve profitability by providing customized services. As it supports customer strategy by developing appropriate marketing campaigns and pricing strategies.
  • E-commerce: These are using data mining business Intelligence to offer cross-sells through their websites. One of the most famous of these is, of course, Amazon. They use sophisticated mining techniques to drive their ‘People who viewed that product. Also liked this’ functionality.
  • Crime Agencies: Beyond corporate applications, Crime prevention agencies use analytics. And Data Mining to spot trends across myriads of data. That should help with everything from where to deploy police manpower. And Particularly who to search at a border crossing. And even which intelligence to take seriously in counter-terrorism activities.