Hi, I am Carlos. I am an MBA student focused on Business Intelligence, Finance, and Data Analytics. I enjoy using SQL to clean data, explore patterns, and generate insights that help businesses make smarter decisions.
This repository highlights a collection of real SQL projects I worked on. Each project includes the business problem, the approach I used, and the insights I found.
Feel free to explore, and if you would like to connect or collaborate, message me on LinkedIn.
• SQL: joins, subqueries, CTEs, aggregations, window functions
• Excel: data modeling, scenario analysis, pivot tables
• Power BI: data modeling, DAX, visual dashboards
• Tableau: visual analytics, mapping, KPI dashboards
• Financial modeling: forecasting, DCF, KPI analysis
| Project | Description | Skills | Link |
|---|---|---|---|
| Sales Trends and Product Analysis | Review January and February sales to identify revenue trends, customer behaviour and product performance | joins, filtering, aggregation | Sales_Analysis/SQL_Sales_Analysis.sql |
| Fortune 500 Analysis | Evaluate business performance patterns across the Fortune 500 | CTEs, case logic, aggregation | Fortune_500_Analysis/Fortune_500_Analysis.sql |
| Logistics Company Analysis | Look at logistics performance to recommend improvements in delivery and operational efficiency | joins, case logic, grouping | Logistics_Analysis/Logistics_Company_Analysis.sql |
| Logistics Data Exploration | Practise joins and filtering on a simplified logistics dataset | table creation, joins, filtering | Logistics_Data/Logistics_Data.sql |
| Telecommunications Services | Explore telecom service usage patterns to identify churn indicators | aggregations, grouping | Telecommunication_Services/Telecommunication_Services.sql |
| Superstore Database | Analyse product and customer behaviour using Superstore data | joins, sorting, aggregation | Superstore_Database/Superstore_Database.sql |
Goal: Understand sales patterns across two monthly datasets and answer questions such as how many unique orders were placed, which products performed best, and which customers placed orders.
Key results: 9268 unique orders in January and 379 iPhone orders in January.
Skills used: joins, aggregation, subqueries. File: Sales_Analysis/SQL_Sales_Analysis.sql
Goal: Explore business performance indicators across Fortune 500 companies.
Focus areas: revenue comparisons, company category breakdown, performance patterns over time.
Skills used: CTEs, aggregation.
Goal: Review logistics performance and examine how operational factors affect outcomes.
Focus areas: shipping patterns, supplier trends, cost structures.
Skills used: joins, case logic, sorting.
Goal: Work with a simplified logistics dataset to practise joins and identify customer and shipment relationships.
Focus areas: customer and shipment tables, join practice, data exploration.
Skills used: table creation, joins, filtering.
Goal: Identify customer behaviour patterns and churn indicators.
Focus areas: monthly usage, customer activity distribution, business patterns.
Skills used: aggregations, grouping.
Goal: Perform product‑level and customer‑level analysis on a Superstore dataset to discover sales trends and customer behaviour.
Focus areas: product performance, customer segmentation, category analysis.
Skills used: joins, sorting, aggregation.
LinkedIn: www.linkedin.com/in/carlos-escudero90
Email: carlos.escud90@outlook.com
Thank you for visiting. If you have questions or want to chat about SQL, BI, or analytics work, feel free to reach out.