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What Technologies Are Used For Data Mining?

In the present age Big Data, Data Science can be applied anywhere. Enterprises across all the verticals are relying heavily on the data-driven smart analytical solutions in Data Science to extract the insights from Big Data. Companies that engage in Data Science can deliver customer centric products, services, and can even analyze the performance of their business processes. With Data Science, businesses can improve their overall business model and increase the profitability.

As a part of the data analysis process, Data Scientists need to make accurate interpretations with large sets of structured & unstructured formats of data. This interpretation will help them in extracting he hidden insights inside data to uncover useful patterns & to find the relationship between different data patterns.  This is where Data Mining becomes crucial. It is an advanced technique in Data Science that would help Data Scientists in making accurate interpretations out of Big Data. Equip yourself with real-world skills in Data Science with our Data Science Training in Hyderabad program.

Technologies Used For Data Mining:

Statistics

Statistical analysis is very crucial when it comes to acquiring a clear idea about data. Both Data Mining & Statistics are closely connected as the Exploratory Data Analysis is performed based on the statistical modelling techniques.

Data Scientists would be making use of different statistical models to characterize and classify the data & it is after this process that Data Mining is done.

Machine Learning

Machine Learning algorithms will be playing a crucial role in the Data Mining process. Data Models that are developed as a part of the Data Mining process would be trained with Machine Learning algorithms to achieve the desired objectives.

Linear Regression, Logistic Regression, Decision Tree, SVM, Naive Bayes, kNN, K-Means, Random Forest, etc are among the most extensively used Machine Learning algorithms in Data Mining.

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