Building a modern data warehouse using SQL Server
This project involves:
Data Architecture: Designing a Modern Data Warehouse Using 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. 🎯 This repository is an excellent resource for professionals and students looking to showcase expertise in:
SQL Development Data Architect Data Engineering ETL Pipeline Developer Data Modeling Data Analytics
Building the Data Warehouse (Data Engineering) Objective Develop a modern data warehouse using SQL Server to consolidate sales data, enabling analytical reporting and informed decision-making.
Specifications 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 analytics 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.