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# Data-Warehousing-and-Advanced-Data-Analytics
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# Retail Events Data Warehouse & Analytics Project
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## Transforming Raw Retail Data into Strategic Insights
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Welcome to my Retail Events Analytics portfolio project! This repository showcases an end-to-end data solution that I designed to help retail businesses make data-driven decisions about their promotional events and campaigns.
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---
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## 📊 Project Overview
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Every retailer faces critical questions about their promotions:
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- "Which campaigns are driving the most revenue?"
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- "Are our discount strategies working effectively?"
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- "How do promotional events impact different product categories?"
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I built this solution to answer these questions through a carefully architected data warehouse and intuitive visualizations that transform complex data into actionable insights.
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---
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## 🏗️ The Architecture Behind the Analysis
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I implemented the industry-standard **Medallion Architecture**, creating a robust data pipeline with three distinct layers:
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![Data Architecture](docs/data_architecture.png)
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### The Data Journey:
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**Bronze Layer**: Raw data ingestion
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- Captures unaltered data from source CSV files
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- Preserves data lineage and enables reprocessing if needed
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- Establishes the foundation for all downstream analytics
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**Silver Layer**: Data refinement
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- Cleanses and standardizes data formats
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- Validates data against business rules
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- Resolves inconsistencies and handles missing values
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- Creates reliable datasets for analysis
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**Gold Layer**: Business intelligence
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- Implements a dimensional star schema for efficient querying
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- Creates pre-aggregated views for common analysis patterns
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- Optimizes for reporting performance and usability
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- Provides business-ready datasets tailored for stakeholder needs
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![Data Model](docs/data_model.png)
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This architecture ensures data quality while maintaining flexibility for evolving business requirements.
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---
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## 💡 Key Analytical Findings
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My analysis uncovered several actionable insights that can directly impact business strategy:
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### Promotion Strategy Effectiveness
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![Promotion Performance Chart](tableau/dashboard.png)
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- **BOGOF Dominance**: The Buy One Get One Free promotion dramatically outperformed all other types, generating over 200,000 units in post-promotion sales—more than double the next best performer
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- **Discount Paradox**: Despite offering the highest monetary value, the 50% OFF promotion showed surprisingly low effectiveness, suggesting consumers respond more to the perception of "getting something free" than equivalent percentage discounts
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- **Pre/Post Comparison**: Analysis of baseline (pre-promotion) sales versus promotional period revealed BOGOF not only had the highest absolute sales but also generated the greatest sales uplift
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- **Strategy Recommendation**: Prioritize BOGOF promotions for high-velocity products where margin can support the strategy
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### Product & Category Performance
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- **Staples Lead**: Atliq Farm Chakki Atta (1KG) emerged as the top-performing product with approximately 80,000 units sold, followed by Atliq Sunflower Oil (1L) at about 70,000 units
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- **Category Dominance**: Grocery & Staples account for 56.6% of total promotional sales, confirming the strategy of using essential items as promotional drivers
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- **Hidden Opportunity**: Despite representing only 7.2% of total sales, the Personal Care category includes high-performing products like Atliq Lime Cool Bathing Bar, suggesting potential for expanding promotion of higher-margin personal care items
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### Campaign & Seasonal Impact
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- **Festival Effect**: The Diwali campaign generated 153,338 units—over twice the sales volume of the Sankranti campaign (73,085 units)
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- **Seasonal Planning**: This 110% performance difference highlights the importance of aligning promotional resources with cultural festivals that drive consumer purchasing behavior
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- **Year-Round Strategy**: Analysis suggests a strategy of major resource allocation to top-performing seasonal campaigns while maintaining smaller, targeted promotions during other periods
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### Geographic Distribution
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- **Market Concentration**: The top three cities (Bengaluru, Chennai, and Hyderabad) account for approximately 60% of total promotional sales (257,813 units)
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- **Expansion Potential**: The steep drop-off to mid-tier cities (Coimbatore through Madurai, each at 30,000-40,000 units) reveals untapped potential for targeted expansion
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- **Localization Opportunity**: Cross-analysis of city performance with promotion types suggests opportunities for city-specific promotional strategies
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---
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## 🛠️ Technical Implementation
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### Data Engineering Excellence
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- **ETL Pipeline**: Custom SQL Server stored procedures that handle incremental data loading
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- **Data Quality Management**: Validation rules enforced during the Silver layer transformation
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- **Performance Optimization**: Indexed views and smart partitioning for query efficiency
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- **Documentation**: Comprehensive data dictionary and lineage tracking
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### Advanced SQL Techniques
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- Window functions for time-series analysis
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- CTEs and subqueries for complex metric calculations
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- Dynamic SQL for flexible reporting parameters
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- Statistical calculations for significance testing
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### Data Visualization
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My Tableau dashboard provides an intuitive interface for business users to:
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- Filter insights by time period, region, or product category
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- Drill down from high-level metrics to granular details
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- Compare campaign performance side-by-side
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- Export findings for stakeholder presentations
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---
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## 📂 Repository Structure
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```
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retail-events-project/
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│
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├── datasets/ # Source data files
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│
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├── docs/ # Documentation and diagrams
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│ ├── data_architecture.drawio.png
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│ ├── data_flow.drawio.png
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│ ├── data_model.drawio.png
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│ ├── promotion_performance.png
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│
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├── scripts/ # SQL implementation
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│ ├── init_database.sql # Database initialization
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│ ├── ddl_bronze.sql # Bronze layer schema
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│ ├── ddl_silver.sql # Silver layer transformations
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│ ├── ddl_gold.sql # Gold layer dimensional model
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│ ├── proc_load_bronze.sql # Data ingestion procedures
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│ ├── proc_load_silver.sql # Data cleansing procedures
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│ ├── gold_views.sql # Analytical views
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│ ├── analysis_queries/ # Advanced analytical queries
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│ ├── promotion_effectiveness.sql
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│ ├── product_performance.sql
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│ ├── campaign_comparison.sql
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│ ├── geographic_analysis.sql
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│
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├── tableau/ # Visualization assets
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│ ├── Retail_Events_Insights.twbx # Interactive dashboard
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│
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├── ad-hoc-requests.pdf # Business requirements
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└── README.md # Project documentation
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```
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---
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## 🚀 Strategic Recommendations
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Based on the comprehensive analysis, I've developed these actionable recommendations:
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1. **Promotion Optimization**
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- Increase BOGOF promotions for high-velocity essential items where margins allow
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- Reconsider 50% OFF promotions or test alternative messaging to improve perception
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- Develop hybrid promotion strategies that combine the psychological appeal of BOGOF with sustainable economics
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2. **Category Expansion**
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- Maintain strong promotional focus on Grocery & Staples as traffic drivers
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- Strategically expand promotions in the Personal Care category, targeting items with demonstrated promotion responsiveness
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- Test bundle promotions that pair high-performing staples with higher-margin personal care items
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3. **Seasonal Allocation**
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- Allocate promotional budget with a 2:1 ratio favoring Diwali over Sankranti based on historical performance
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- Develop Diwali-specific product bundles focused on top-performing categories
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- Create targeted smaller promotions for Sankranti with region-specific approaches
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4. **Geographic Strategy**
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- Maintain strong promotional presence in top-performing cities
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- Develop tailored expansion strategies for mid-tier cities showing growth potential
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- Consider city-specific promotion types based on local performance data
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---
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## 🔍 Key Takeaways
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This project demonstrates my ability to:
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- Transform business questions into technical requirements
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- Architect scalable data solutions following industry best practices
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- Implement robust ETL processes with proper error handling
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- Apply advanced analytical techniques to derive meaningful insights
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- Translate data findings into concrete business recommendations
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- Bridge the gap between technical implementation and business value
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---
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## 🔗 Connect With Me
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I'm passionate about helping businesses leverage their data assets through thoughtful architecture and insightful analytics.
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**Sai Suraj M.V.V.**
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Data Analytics Specialist
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📧 [saisurajmvv@gmail.com](mailto:saisurajmvv@gmail.com)
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🔗 [LinkedIn](https://www.linkedin.com/in/saisurajmatta/)
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🌐 [Portfolio](https://saisurajmatta.github.io/Portfolio)
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💻 [GitHub](https://github.com/SaiSurajMatta)
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*Looking for a data professional who can turn your business questions into actionable insights? Let's connect!*

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