Prakash Lakkakula Portfolio

In this project, I cleaned up housing data in SQL Server to make it accurate and reliable. I fixed missing information, made sure everything was in a consistent format, and got rid of any duplicate entries. I also handled unusual data and transformed it to be more useful. I documented all the steps I took and now we have a clean dataset ready for analysis, making it easier to make informed decisions.

In this project, I used a COVID dataset to show off my proficiency with SQL-based data exploration. I examined important indicators including total cases, global data, total recoveries, and deaths using SELECT, GROUP BY, and JOIN commands, revealing regional patterns and variances. I provided a thorough analysis by using JOIN procedures to incorporate more data and using aggregate functions.

In this project, I used the same COVID-19 dataset that was previously utilized for data exploration using SQL. I created different visualizations and finally developed a dashboard as depicted in the image below.

In this project, I utilized the Movie dataset to calculate the correlations between each variable to identify which elements are most correlated with the gross collection. It was subsequently discovered that the "votes" and "budget" variables exhibit a high correlation with the gross collection.