In this project, I worked with various data analysis tools, including SQL, Power BI, and Excel, to derive insights from the dataset ocd_patient_dataset.csv which I obtained from Kaggle.

Firstly, in SQL, I broke down the analysis into 5 stages. On the first stage, I calculated the total number of male and female patients and the average 'Y-BOCS Score (Obsessions)' for each gender. On the second stage, I counted the number of patients for each ethnicity and computed the average 'Y-BOCS Score (Obsessions)' for each ethnicity. On the third stage, I grouped patients by the month of their OCD diagnosis and counts the number of patients diagnosed in each month. On the forth stage,I identified the most common types of obsessions among patients and calculated the average 'Y-BOCS Score (Obsessions)' for each obsession type. On the last step, I identified the most common types of compulsions among patients and calculated the average 'Y-BOCS Score (Obsessions)' for each compulsion type.Uploading Health data analysis.sql…

Secondly, I imported five datasets obtained in SQL into Power BI and made five graphs to visualize the five stages of analysis in SQL.

Finally, I made five graphs in Excel to illustrate the five datasets to finalize the analysis.Health data analysis.xlsx

SQL helped me manipulate the data and perform some feature engineering. Excel and Power BI assisted me in visualizing my findings in a way that is easy for stakeholders to consume.