Description:
The goal of this project was to use Excel functionality to analyze data about Adidas's product sales in the United States, which contain information in 9652 rows and 14 columns for the fiscal years 2020 and 2021. The goal was to visualize the data, prepare different types of reports, and interactive dashboard.
Reports and conclusions:
Original dataset:
adidas-us-sales.xlsx
Skills:
Analytical thinking, data cleaning, data analysis, data visualization.
Hard skills:
Excel, Pivot Tables, Formulas, Functions, Charts, Dashboards, Slices, Pivot Charts.
Results:
An analysis of financial data on the sale of Adidas products in the USA for 2020 and 2021 was performed. Reports and dashboard were created.
Description:
This Excel dashboard presents a comprehensive overview of sales performance metrics, for a US-based industrial supply company, providing insights into key aspects of the sales process. It offers a visually appealing and interactive interface to analyze sales data effectively.
Components:
- Sales Overview: Summary of total sales, top-performing products, regions, or sales representatives.
- Sales Trends: Visual representation of sales trends over time, highlighting peaks and troughs.
- Product Performance: Analysis of individual product performance, including sales volume, revenue, and profitability.
- Regional Analysis: Breakdown of sales by region or territory, identifying areas of strength and opportunities for improvement.
- Sales Rep Performance: Evaluation of sales representatives' performance, showcasing top performers and areas needing improvement.
- Goal Tracking: Comparison of actual sales against predefined sales targets or goals.
- Interactive Features: Filters, slicers, or dropdown menus for users to customize data views based on specific criteria.
Skills:
Excel, Pivot Tables, Formulas, Functions, Charts, Dashboards, Slicers, Interactive Features.
Results:
The sales performance dashboard provides actionable insights into sales trends, product performance, regional analysis, and sales representative performance, facilitating informed decision-making and strategic planning.
Description:
I explored Python in Pycharm by analyzing worldwide sugarcane production data. Determined average sugarcane production yield using Python. Link to raw data set
Skills:
Excel, Pivot Tables, Formulas, Python, Pycharm
Below are some data visualizations I've made. I enjoy bringing data to life and making it visually appealing.
Operation Costs By Department for Nationally-Recognized Construction Company. Fiscal Year 2018. Generated w/Excel.
Server CPU Load Report for SysAdmin Team, weekly comparison, American General Tool Group. Generated w/Excel.
Population overlayed by life expentancy. Per Country and Continent 2018. Used Tableau. Link to raw data set