Advanced MySQL to analyze marketing campaigns. Where our website traffic is coming from, how different sources perform in terms of traffic volume and conversion rates, and how we can adjust bids to optimize our budgets among other busyness request.
This repository helps you gain valuable insights from your sales data using SQL and RFM analysis and segment customers based on their RFM score and the churn rate.
Pizza Sales Report project, where we leverage SQL for data analysis and Power BI for creating interactive visualizations. This project provides in-depth insights into pizza sales data, including daily and monthly trends, sales by pizza category and size, and identifying top-selling pizzas based on revenue, quantity, and total orders.
Explore pizza sales trends via SQL analysis and dynamic Power BI dashboards. Discover daily/monthly insights, category-based sales, and top-selling pizzas by revenue and quantity.
The Fifa-Dataset-SQL-Data-Analysis project uses SQL to explore FIFA player data, analyzing performance and attributes to extract meaningful insights on player statistics, trends, and patterns in football.
📡 Real-time data pipeline with Kafka, Flink, Iceberg, Trino, MinIO, and Superset. Ideal for learning data systems.
Containing data analysis with SQL projects on various topic
An example for analyzing time-event data
This project aims to create a comprehensive data analysis system based on the Wide World Importers (WWI) database.
SQL project analyzing MLB schools, salaries, careers, and comparisons. Explores top schools, team spending, player career spans, team loyalty, batting hand trends, and decade-by-decade height/weight changes using advanced queries and analytics.
Explore and analyze data with this SQL-based project. Utilizing SQL queries, joins, aggregations, and subqueries, uncover valuable insights in the dataset. Access the SQL scripts for detailed analysis and insights extraction.
10 ad-hoc business requests solved using SQL queries for Consumer Goods (FMCG) domain. Includes query optimization, schema documentation, and actionable business insights
PostgreSQL data pipeline for NFL play-by-play analytics with full ETL, schema design, and optimized SQL views.
🦆 Batch data pipeline with Airflow, DuckDB, Delta Lake, Trino, MinIO, and Metabase. Full observability and data quality.
SQL-based Financial KPI dashboard with optimized Power BI queries.
An advanced analytical extension of the SQL Data Warehouse project focusing on customer profiling, sales segmentation, and product analysis. Built using Gold layer views, this project demonstrates how to extract actionable insights using SQL analysis techniques such as ranking, segmentation, cumulative growth, and time-based comparisons.
End-to-end SQL analytics for market expansion. Designed schema, applied normalization, and used advanced SQL (CTEs, Window Functions, Cohorts) to analyze sales. Created a composite city score and 30+ metrics to recommend top cities for a coffee company's physical store rollout.
End-to-end data pipeline with Python orchestration, PostgreSQL Medallion layers, metadata + invalid-record logging, and CI/CD (pytest + flake8 on GitHub Actions).
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