Anas Maichouf
E-Commerce Data Analysis Project using SQL and Tableau
This project involves an in-depth analysis of an e-commerce platform’s data to gain insights into customer behavior, sales performance, product popularity, payment methods, and delivery performance. The goal is to provide actionable insights that can help improve business strategies, enhance customer experience, and optimize operations.
Data Sources:
The analysis utilizes the following CSV files:
- Customers.csv: Customer details including unique IDs, locations, and state codes.
- Geolocation.csv: Geolocation data including latitude, longitude, and zip codes.
- Order_Items.csv: Order item details such as product IDs, seller IDs, prices, and shipping information.
- Orders.csv: Order information including status, timestamps, and delivery dates.
- Payments.csv: Payment details including payment types, installment information, and values.
- Products.csv: Product details including category names, dimensions, and weights.
- Sellers.csv: Seller information including locations and state codes.
Tools and Technologies:
- SQL: For data extraction and preparation.
- Tableau: For data visualization and dashboard creation.
Click here to see Tableau Visualization// Click here to see SQL Query
Bank Loan Analysis Project using SQL and Power BI
In this project, I developed a comprehensive analysis system for bank loans utilizing SQL for data management and Power BI for visualization. The primary goal was to provide insightful analytics on loan applications, funded amount, and received amount, average interest rate and average DTI (Debt to Income).
Project Highlights:
- Data Management with SQL: I used SQL to clean and organize the bank loan data, learning how to write basic queries to extract relevant information.
- Basic Dashboards in Power BI: Created simple, yet effective dashboards in Power BI to visualize loan data, including charts and graphs.
- Customer Analysis: Conducted a basic analysis of customer data to identify trends based on criteria like loan type, funded amounts and repayment status.
- Introductory Risk Assessment: Implemented a straightforward risk assessment to visualize potential loan defaults, helping to identify high-risk loans.
- Tracking Loan Performance: Developed simple visualizations to track loan performance over time, providing a clear picture of trends and patterns.
This project was a great learning experience, helping me build foundational skills in data analysis and visualization, and demonstrating how to turn raw data into meaningful insights.
Walmart Sales Analysis Project using SQL and Power BI
This project focuses on analyzing Walmart sales data to derive meaningful insights that can help understand sales performance and trends. Using SQL for data management and Power BI for data visualization, the project aims to provide a comprehensive overview of sales metrics, identify key patterns, and highlight areas for potential improvement. This hands-on project has been a great opportunity to apply data analysis skills and create interactive visualizations that offer valuable business insights.
Technologies Used:
- SQL: For data querying, cleaning, and management.
- Power BI: For creating introductory-level reports and interactive visualizations.
Revenue Performance Analysis Project using SQL and Power BI
In this project, I analyzed revenue performance data to gain insights into various aspects of revenue generation, including regional performance, client contributions, and departmental revenue. Using SQL for data processing and Power BI for visualization, I created a comprehensive analysis to help understand and track revenue trends.
Project Highlights:
- Data Processing with SQL: Extracted, cleaned, and structured revenue data from various sources using SQL. Wrote queries to pull relevant information and prepare the dataset for analysis.
- Interactive Dashboards in Power BI: Developed dynamic dashboards in Power BI to visualize key revenue metrics such as revenue by region, revenue by client, month-on-month revenue growth, and revenue by department.
- Revenue by Region: Analyzed and visualized revenue data across different regions to identify high-performing areas and regions with growth potential.
- Revenue by Client: Examined revenue contributions from different clients, highlighting major clients and identifying opportunities for enhancing client relationships.
- Month-on-Month Revenue Growth: Tracked and visualized month-on-month revenue changes to understand growth patterns and seasonal trends.
- Revenue by Department: Evaluated the revenue performance of various departments, identifying strengths and areas for improvement within the organization.
- Performance Tracking: Implemented visualizations to monitor overall revenue performance over time, providing clear insights into revenue trends and helping inform strategic decisions.
Technologies Used:
- SQL: For data querying, cleaning, and management.
- Power BI: For creating introductory-level reports and interactive visualizations.
Cars Sales Analysis Project using SQL and Power BI
In this project, I analyzed car sales data to uncover insights into sales performance, customer preferences, and ratings. Using SQL for data handling and Power BI for visualization, I created a detailed analysis to understand trends in car sales and customer feedback.
Project Highlights:
- Data Processing with SQL: Extracted, cleaned, and organized car sales data using SQL. Crafted queries to retrieve essential information for analysis.
- Interactive Dashboards in Power BI: Developed dynamic dashboards in Power BI to visualize key metrics such as units sold by year, units sold by car options, and customer ratings.
- Units Sold by Year: Analyzed yearly sales data to identify trends and growth patterns in car sales over time.
- Units Sold by Car Options: Examined sales based on different car options (e.g., color, model, features) to understand customer preferences and popular configurations.
- Customer Ratings Analysis: Investigated customer ratings to assess satisfaction levels and identify areas for improvement in product offerings.
- Performance Tracking: Implemented visualizations to track overall sales performance and customer feedback, providing clear insights to support marketing and sales strategies.
Technologies Used:
SQL: For comprehensive data querying, cleaning, and management. Power BI: For creating interactive and informative reports and visualizations.