I'm thrilled to present my first ever project, a thorough sales dashboard for a business that offers three different product lines.
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Sales by Category: A sales funnel with the most popular subcategories displayed.
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Yearly Profit: A line graph that shows the annual profits for every category from 2014 to 2017.
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Sales by State: This map illustrates how sales are distributed among the states.
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Consumer Count by Year: This bar graph, which peaked in 2017, illustrates annual consumer patterns.
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Top 5 Clients: A pie chart displaying the top five clients, with the highest at $5,918.59.
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Monthly Sales: The performance of monthly sales is shown in an area chart. Clear insights into sales patterns, top-performing products, and business prospects are offered by this dashboard.
Here I go with my second one in a row.
"Analyzing Retail Sales Data to Enhance Coffee Shop Performance". ☕💰
The main objective of this project is to thoroughly analyze retail sales data specific to a coffee shop. By closely examining various aspects such as customer purchasing behaviors, peak sales times, product popularity, and seasonal trends, the project aims to uncover actionable insights that can enhance business operations.
Utilizing advanced data analytics techniques, the project will pinpoint key performance indicators that impact revenue growth and customer satisfaction. The insights gained from this analysis will guide strategic decisions, helping the coffee shop optimize its menu, improve marketing efforts, and streamline service delivery.
This data-driven approach aims to improve the overall performance of the coffee shop, ensuring it not only meets but exceeds market expectations. This will help build a loyal customer base and increase profitability.
Analysis:
- How do sales fluctuate based on the day of the week and the time of day?
- Are there specific peak times for sales activity?
- What is the total sales revenue for each month?
- How do sales differ across various store locations?
- What is the average order value per customer?
- Which products are the top sellers in terms of quantity and revenue?
- How do sales differ by product category and type? 📌 Objective:
The Bank Loan Report project delves into monitoring and evaluating a bank's lending activities, offering comprehensive insights into loan-related metrics. This Excel dashboard aims to support data-driven decision-making and strategic planning.
📌 Key Performance Indicators:
▪️ Total Loan Applications ▪️ Total Funded Amount ▪️ Total Amount Received ▪️ Average Interest Rate ▪️ Average Debt-to-Income Ratio
📌 Summary Dashboard:
✔️ Good Loan vs. Bad Loan
▪️ Good Loan Application Percentage ▪️ Good Loan Applications ▪️ Good Loan Funded Amount ▪️ Good Loan Total Received Amount ▪️ Bad Loan Application Percentage ▪️ Bad Loan Applications ▪️ Bad Loan Funded Amount ▪️ Bad Loan Total Received Amount
📌 Overview Dashboard:
✔️ Charts
▪️ Monthly Trends by Issue Date (Line Chart) ▪️ Regional Analysis by State (Map Chart) ▪️ Loan Term Analysis (Donut Chart) ▪️ Employee Length Analysis (Bar Chart) ▪️ Loan Purpose Breakdown (Bar Chart) ▪️ Home Ownership Analysis (Tree Map)
🎯Insights and Conclusions from the Bank Loan Case Study:
- Analyzed bank loan data, noting a 13.0% month-over-month growth in funded amounts and a 15.8% increase in total amounts received.
- Reported key metrics, including a 3.5% average interest rate increase and a 2.7% improvement in the debt-to-income ratio month-over-month, aiding strategic planning.
- Monitored the loan portfolio, highlighting an 86.2% good loan rate, and provided insights for risk management and credit evaluation.
- Conducted segmentation analysis by geography, loan purpose, and customer profiles, contributing to targeted marketing and product development.