I am a Data professional (Big Data), and my specialization lies in conducting data analysis, generating dashboards and reports, developing data models, and providing performance insights. My proficiency in converting business requirements into efficient operational dashboards and performance-oriented insights enables me to facilitate seamless communication with stakeholders, thereby ensuring clarity and precision in the project's execution.
Hard Skills: SQL, Power Bi, Tableau, Python, R-Studio, and Microsoft Suite
My LinkedIn ProfileThe purpose of this project was to transform the raw data of COVID-19 into a usable and organized database, through the detection and correction of inaccurate or irrelevant records in the SQL Server. To ensure accuracy, various tests and checks were performed on the data to isolate any discrepancies or outliers. The data was then organized and structured to create a cleaned database ready for analysis.
The main objective of this project was to revamp the raw data from two hotels, delete any inaccurate and unnecessary information from the database in SQL Server for better organization, and facilitate data analysis and visualization.
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This data analysis of Spotify data examined the relationships between different music genres and levels of popularity. The analysis gives insights on followers, song popularity, the correlation between metrics and so much more.
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Here, I worked on sales raw data where I did data manipulation, analysis, and visualization with PowerBi, highlighting patterns and trends in the data to help stakeholders gain quick insights.
In this project, I made a graphical representation of the covid-19 data that was previously cleaned, highlighting patterns and trends in the data to help stakeholders gain quick insights.
This project utilized Python to analyze a set of raw world movie data. A range of data manipulation techniques were used to gain insights, including aggregation, filtering, sorting and indexing. The analysis and its findings were then summarized in a comprehensive report.
This project utilized Python to analyze world movie data. Data exploration, cleaning, manipulation and visualization were used to gain insight and a report was generated to summarize findings. Data manipulation techniques included aggregation, filtering, sorting and indexing.
After undertaking a careful and rigorous data analysis process with Power BI, I was able to replicate the Spotify project I had previously completed in Python. I meticulously cleaned, explored, and analyzed the data before creating a suite of compelling visualizations to effectively illustrate the findings.
In this project, I used the previous cleaned data from SQL to created a graphical representation leveraging various graphical charts and plots, such as line graphs, pie charts, and slicers to effectively visualize the data and its salient features providing stakeholders with insights and trends.
