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SQL Data-Warehouse-Project

Welcome to the Data Warehouse and Analytics Project repository! 🚀

This project demonstrates a comprehensive data warehousing and analytics solution, from building a data warehouse to generating actionable insights. Designed as a portfolio project, it highlights industry best practices in data engineering and analytics.

Data Architecture

The data architecture for this project follows Medallion Architecture Bronze, Silver, and Gold layers.

  1. Bronze Layer: Stores raw data as-is from the source systems. Data is ingested from CSV Files into SQL Server Database.

  2. Silver Layer: This layer includes data cleansing, standardization, and normalization processes to prepare data for analysis.

  3. Gold Layer: Houses business-ready data modeled into a star schema required for reporting and analytics.

Project Overview

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.

Project Requirements

Building the Data Warehouse (Data Engineering)

Objective

Developed 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. BI: Analytics & Reporting (Data Analysis) Objective 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.

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