Retail Events Data Warehouse & Analytics Project

Transforming Raw Retail Data into Strategic Insights

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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📊 Project Overview

Every retailer faces critical questions about their promotions:

• "Which campaigns are driving the most revenue?"
• "Are our discount strategies working effectively?"
• "How do promotional events impact different product categories?"

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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🏗️ The Architecture Behind the Analysis

I implemented the industry-standard Medallion Architecture, creating a robust data pipeline with three distinct layers:

The Data Journey:

Bronze Layer: Raw data ingestion

• Captures unaltered data from source CSV files
• Preserves data lineage and enables reprocessing if needed
• Establishes the foundation for all downstream analytics

Silver Layer: Data refinement

• Cleanses and standardizes data formats
• Validates data against business rules
• Resolves inconsistencies and handles missing values
• Creates reliable datasets for analysis

Gold Layer: Business intelligence

• Implements a dimensional star schema for efficient querying
• Creates pre-aggregated views for common analysis patterns
• Optimizes for reporting performance and usability
• Provides business-ready datasets tailored for stakeholder needs

This architecture ensures data quality while maintaining flexibility for evolving business requirements.

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💡 Key Analytical Findings

My analysis uncovered several actionable insights that can directly impact business strategy:

Promotion Strategy Effectiveness

• 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
• 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
• 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
• Strategy Recommendation: Prioritize BOGOF promotions for high-velocity products where margin can support the strategy

Product & Category Performance

• 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
• Category Dominance: Grocery & Staples account for 56.6% of total promotional sales, confirming the strategy of using essential items as promotional drivers
• 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

Campaign & Seasonal Impact

• Festival Effect: The Diwali campaign generated 153,338 units—over twice the sales volume of the Sankranti campaign (73,085 units)
• Seasonal Planning: This 110% performance difference highlights the importance of aligning promotional resources with cultural festivals that drive consumer purchasing behavior
• Year-Round Strategy: Analysis suggests a strategy of major resource allocation to top-performing seasonal campaigns while maintaining smaller, targeted promotions during other periods

Geographic Distribution

• Market Concentration: The top three cities (Bengaluru, Chennai, and Hyderabad) account for approximately 60% of total promotional sales (257,813 units)
• 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
• Localization Opportunity: Cross-analysis of city performance with promotion types suggests opportunities for city-specific promotional strategies

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🛠️ Technical Implementation

Data Engineering Excellence

• ETL Pipeline: Custom SQL Server stored procedures that handle incremental data loading
• Data Quality Management: Validation rules enforced during the Silver layer transformation
• Performance Optimization: Indexed views and smart partitioning for query efficiency
• Documentation: Comprehensive data dictionary and lineage tracking

Advanced SQL Techniques

• Window functions for time-series analysis
• CTEs and subqueries for complex metric calculations
• Dynamic SQL for flexible reporting parameters
• Statistical calculations for significance testing

Data Visualization

My Tableau dashboard provides an intuitive interface for business users to:

• Filter insights by time period, region, or product category
• Drill down from high-level metrics to granular details
• Compare campaign performance side-by-side
• Export findings for stakeholder presentations

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📂 Repository Structure

retail-events-project/
│
├── datasets/                       # Source data files
│
├── docs/                           # Documentation and diagrams
│   ├── data_architecture.drawio.png
│   ├── data_flow.drawio.png
│   ├── data_model.drawio.png
│   ├── promotion_performance.png
│
├── scripts/                        # SQL implementation
│   ├── init_database.sql           # Database initialization
│   ├── ddl_bronze.sql              # Bronze layer schema
│   ├── ddl_silver.sql              # Silver layer transformations
│   ├── ddl_gold.sql                # Gold layer dimensional model
│   ├── proc_load_bronze.sql        # Data ingestion procedures
│   ├── proc_load_silver.sql        # Data cleansing procedures
│   ├── gold_views.sql              # Analytical views
│   ├── analysis_queries/           # Advanced analytical queries
│      ├── promotion_effectiveness.sql
│      ├── product_performance.sql
│      ├── campaign_comparison.sql
│      ├── geographic_analysis.sql
│
├── tableau/                        # Visualization assets
│   ├── Retail_Events_Insights.twbx # Interactive dashboard
│
├── ad-hoc-requests.pdf             # Business requirements
└── README.md                       # Project documentation

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🚀 Strategic Recommendations

Based on the comprehensive analysis, I've developed these actionable recommendations:

1. Promotion Optimization

   • Increase BOGOF promotions for high-velocity essential items where margins allow
   • Reconsider 50% OFF promotions or test alternative messaging to improve perception
   • Develop hybrid promotion strategies that combine the psychological appeal of BOGOF with sustainable economics

2. Category Expansion

   • Maintain strong promotional focus on Grocery & Staples as traffic drivers
   • Strategically expand promotions in the Personal Care category, targeting items with demonstrated promotion responsiveness
   • Test bundle promotions that pair high-performing staples with higher-margin personal care items

3. Seasonal Allocation

   • Allocate promotional budget with a 2:1 ratio favoring Diwali over Sankranti based on historical performance
   • Develop Diwali-specific product bundles focused on top-performing categories
   • Create targeted smaller promotions for Sankranti with region-specific approaches

4. Geographic Strategy

   • Maintain strong promotional presence in top-performing cities
   • Develop tailored expansion strategies for mid-tier cities showing growth potential
   • Consider city-specific promotion types based on local performance data

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🔍 Key Takeaways

This project demonstrates my ability to:

• Transform business questions into technical requirements
• Architect scalable data solutions following industry best practices
• Implement robust ETL processes with proper error handling
• Apply advanced analytical techniques to derive meaningful insights
• Translate data findings into concrete business recommendations
• Bridge the gap between technical implementation and business value

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🔗 Connect With Me

I'm passionate about helping businesses leverage their data assets through thoughtful architecture and insightful analytics.

Sai Suraj M.V.V.
Data Analytics Specialist

📧 [email protected]
🔗 LinkedIn
🌐 Portfolio
💻 GitHub

Looking for a data professional who can turn your business questions into actionable insights? Let's connect!