Abstract

Data mining lies at the interface of statistics, pattern recognition, and machine learning. An organized collection of data and proper data visualization are the main prerequisites of data mining. Proper use of data mining techniques will help to identify important patterns and relationships in a dataset. In this paper, we implement a data mining algorithm on mental health data and find the most important attributes that trigger issues with mental health treatment. For this study we used Microsoft Excel for data preparation and filtering, SQL server as the data storage, and SQL Server Analysis Service (SSAS) for building the data mining model. This is an important process which can help organizations provide a comfortable environment to employees that facing issues with mental health treatment.

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