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Different Approaches For Data Mining In Data Science

Data Mining is an advanced technique in Data Science that works towards extracting hidden insights & uncovers patterns from the large sets of Big Data. This technique also helps in finding the unknown correlations between different datasets. Data Mining is a must to have skill set in the inventory of a Data Scientist. To effectively handle the skills in Data Mining, knowledge of Machine Learning Algorithms, Statistical Modelling, Data Modelling & AI would be very crucial.  

The process of Data Mining is also known as Knowledge Discovery. The applications of Data Mining will help the enterprises to benefit from accurate fraud detection, personalized marketing, risk analysis and scientific discovery, etc. Work towards leveraging real-world skills in relation to working on Data Mining technique in Data Science with the help of our advanced Data Science Training In Hyderabad program.

Now, let’s look at the different techniques & challenges in Data Mining.

  • Outer Detection

This approach refers to observation of data items in the dataset that doesn’t match with the expected pattern. This form of approach in Data Mining is very crucial when it comes to identifying unusual behaviour from the data patterns. So, this approach will be crucial for as intrusion, detection, fraud or fault detection, etc.

  • Sequential Patterns

This is a prominent technique that helps the analysts in identifying similar data patterns & trends from Big Data. This technique will be ideal when it comes to analyzing in transactional data during a fixed time period.

  • Prediction

This is an advanced Data Mining technique that is a combination of trends, sequential patterns, clustering, classification, & other Data Mining techniques. This type of Data Mining technique analyzes the historical & present data to make accurate predictions.

Know more in-depth about the other types of prominent Data Mining techniques like Clustering, Regression, Classification, Association Rule, etc by being a part of Kelly Technologies Data Science training program.

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