Data mining is the exploration and analysis of a large amount of data to discover meaningful patterns and rules. It involves finding anomalies, patterns, and correlations within large datasets in order to predict outcomes.
Data mining is also known as Knowledge Discovery in Data (KDD).
This step involves understanding the business use case and how data mining can help to improve strategies.
The data is collected from several sources for analysis. This data is then visualized and understood for further analysis.
This step involves data cleaning. It is important to maintain the integrity and security of data. Care should also be taken that no important information is overlooked during data cleaning.
Mathematical models are used to find patterns in the data using sophisticated data tools.
The findings from the previous step are evaluated and compared with business objectives to determine if they should be deployed across the organization.
This step involves sharing the findings and taking necessary measures to run the business efficiently.
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