Conducted an in-depth Analysis of Amazon sales data to uncover significant trends and customer preferences.
Leveraged Python's robust libraries, including Pandas, Matplotlib, and Seaborn, to perform meticulous Data Cleaning, Comprehensive Analysis, and Insightful Visualizations.
Through the application of advanced data techniques, I identified key factors influencing sales performance.The analysis culminated in detailed
reports and visual dashboards that provided actionable insights for stakeholders.
The project not only demonstrated my ability to handle complex datasets but also highlighted my proficiency in translating data into practical business strategies.
This version flows smoothly while emphasizing the critical aspects of your work.
Successfully imported, cleaned, and integrated Ecommerce Sales Data from multiple sources into Power BI,
enabling a comprehensive and unified view of business performance.
Leveraged advanced data modeling techniques to create interactive
dashboards and detailed reports that provide deep insights into Sales Trends,
Customer Behaviour, and Market Dynamics.
These visualizations empowered the
sales and marketing teams to make data-driven decisions, leading to the
refinement of sales strategies, optimization of product listings, and the execution of highly targeted marketing campaigns.
As a result, these efforts contributed to a significant increase in sales performance, enhanced customer satisfaction, and stronger market positioning.
Leveraged Power BI to perform an extensive Analysis of HR data, transforming complex and disparate datasets into cohesive,
organizational efficiency, talent management, and overall business success.
interactive dashboards that illuminated key HR metrics such as employee turnover, retention rates, recruitment efficiency,
and workforce diversity.
By employing advanced data modeling and visualization techniques, the dashboards distilled large
volumes of data into actionable insights that clearly identified trends and areas requiring attention.
These insights empowered
the HR team to streamline processes, enhance employee engagement strategies, and make informed decisions grounded in data, ultimately driving improvements in
organizational efficiency, talent management, and overall business success.
This project employs Python and Machine Learning to predict Titanic passenger survival using the Kaggle dataset.
It begins with data preprocessing, including handling missing values and encoding categorical variables.
The dataset is split into training and testing sets using a train-test split to ensure accurate model evaluation.
Predictive models are trained with Logistic Regression and assessed on the test set. Performance is measured using accuracy.
The project also investigates factors influencing survival rates, such as passenger class and age.
This approach demonstrates the practical application of machine learning in predictive analytics, showcasing how data-driven insights can reveal important patterns and enhance decision-making.
For the Maven Halloween Challenge, I developed an engaging interactive Power BI dashboard that identifies the top three candies for Halloween by analyzing votes on 85 candy types.
The dashboard not only visualizes key metrics, such as win percentage and candy attributes, but also tells a story about consumer preferences.
It features the top three candies based on popularity, a scatter plot comparing price versus win percentage, and a bar chart showcasing candy attribute distribution.
Interactive slicers allow users to filter by price, win percentage, and sugar content, making data exploration fun and insightful.
This project highlights my skills in data visualization and analysis while ensuring that every trick-or-treater can enjoy a sweet experience with the best treats on Halloween!
Experienced in creating structured and semantic HTML documents.
Proficient in designing responsive and visually appealing layouts using CSS.
Skilled in enhancing interactivity and dynamic behavior of web pages with JavaScript.
Experienced in scripting and automating tasks with Python.
Experienced in writing complex SQL queries for efficient data retrieval.
Skilled in designing interactive and insightful reports using Power BI tools.
Proficient in designing and implementing machine learning models for data-driven predictions.
Proficient in leveraging Excel for data analysis, including advanced formulas, pivot tables, and data visualization.
