Welcome to the Data Warehouse and Analytics Project repository!
This project demonstrates a comprehensive data warehousing and analytics solution, from building a datawarehouse to generating actionable insights. Designed as a portfolio project that highlights industry best practices in data engineering and analytics.
This project involves:
- Data Architecture: Designing a modern data warehouse using the Medallion architecture bronze, silver, and gold layers.
- ETL Pipelines: Extracting, transforming, and loading data from source systems into the warehouse.
- Data Modeling: Developing fact and dimension tables optimized for analytical queries.
- Analytics & Reporting: Creating SQL-based reports and dashboards for actionable insights.
Develop a modern data warehouse using SQL Server to consolidate sales data, enabling analytical reporting and informed decision-making.
- Data Sources: Import data from two source systems (ERP and CRM) provided as CSV files.
- Data Quality: Cleanse and resolve data quality issues prior to analysis.
- Integration: Combine both sources into a single, user-friendly data model designed for analytical queries.
- Scope: Focus on the latest dataset only; historization of data is not required.
- Documentation: Provide clear documentation of the data model to support both business stakeholders and analytical teams.
Develop SQL-based analytics to deliver detailed insights into:
- Customer Behavior
- Product Performance
- Sales Trends
These insights empower stakeholders with key business metrics, enabling strategic decision-making. For more details, refer to the Data Catalog
The data architecture for this project follows the Medallion Architecture Bronze, Silver, and Gold layers:
- Bronze Layer: Stores raw data as-is from the source systems. Data is ingested from CSV files into SQL Server Database.
- Silver Layer: This layer includes data cleansing, standardization, and normalization processes to prepare data for analysis.
- Gold Layer: Houses business-ready data modeled into a star schema required for reporting and analytics.
The hierarchy of this project is listed and described below.
📦 sql-data-warehouse-project
├─ LICENSE # License information for the repository
├─ README.md # Project overview and instructions
├─ datasets # Raw datasets used for the project (ERP and CRM data)
│ ├─ source_crm
│ │ ├─ cust_info.csv
│ │ ├─ prd_info.csv
│ │ └─ sales_details.csv
│ └─ source_erp
│ ├─ CUST_AZ12.csv
│ ├─ LOC_A101.csv
│ ├─ PX_CAT_G1V2.csv
├─ docs
│ └─ data_catalog.md # Catalog of datasets, including field descriptions and metadata
├─ scripts # SQL scripts for ETL and transformation
│ ├─ bronze
│ │ ├─ ddl_bronze.sql # SQL scripts for extracting and loading raw data
│ │ └─ procedure_load_bronze.sql
│ ├─ gold
│ │ └─ ddl_gold.sql # SQL scripts for creating analytical models
│ ├─ init_database.sql
│ └─ silver
│ ├─ ddl_silver.sql # SQL scripts for cleaning and transforming data
│ └─ procedure_load_silver.sql
└─ tests
└─ quality_checks_silver.sql # Test scripts and quality files for the silver layer
This project is licensed under the [MIT License]. You are free to use, modify, and share this project with proper attribution
Hi there! I'm Ayodele Benjamin Esan. I hold a doctorate in Electrical Engineering with a focus on Deep Reinforcement Learning applications in Energy Systems. I'm in love with Data Engineering and on a mission to build systems that feed AI agents high-quality data to make informed decisions! Feel free to connect with me on:
