Introduction
When success outpaces infrastructure, even premium brands can find themselves drowning in data they can’t actually use. This fashion powerhouse had cracked the code on multi-channel distribution and premium positioning, but their data lived in silos across e-commerce platforms, logistics providers, marketing tools, and internal systems. Every platform spoke a different language, with different formats and update cycles. The result?
Million-dollar decisions were being made on gut instinct rather than unified intelligence. We built them a decision-making engine that thinks like a business and performs like a machine.
Challenges
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Fragmented Data Sources
Information scattered across 11+ platforms with inconsistent formats, update cycles, and business logic definitions.
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No Existing Data Foundation
Greenfield project requiring deep stakeholder engagement to understand processes and build unified models from scratch.
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Inconsistent Business Definitions
Order status, product IDs, and customer data varied significantly across platforms, requiring careful mapping and standardization.
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Daily Refresh Requirements
Business demanded fresh data every 24 hours for agile decision-making in fast-moving fashion industry.
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Data Quality & Trust Issues
Lack of validation testing meant unreliable outputs that couldn’t support strategic business decisions.
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Security & Compliance Needs
Role-based access controls and PII protection required while maintaining analytical capabilities.
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Cost Optimization Pressure
Multiple cloud tools and daily processing threatened budget escalation without proper optimization strategies.
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Future-Proof Architecture
Needed modular, maintainable code structure to handle rapid business evolution and new channel additions.
Solution
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Unified ELT Pipelines
Built end-to-end automated data ingestion from all sources into centralized Snowflake environment with daily refresh scheduling.
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Dimensional Data Modeling
Created business-aligned models across sales, marketing, logistics, and web traffic enabling self-service analytics.
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DBT-Powered Development
Implemented modular, reusable SQL models with built-in testing and version control for maintainable data transformation.
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Data Standardization Layer
Harmonized definitions for order status, product identifiers, and customer data across all platforms for unified reporting.
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Enterprise Security Framework
Deployed role-based access controls, data masking, and PII protection in Snowflake while enabling cross-team collaboration.
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Automated Orchestration
Used Airflow for workflow monitoring, failure handling, and intelligent alerting to ensure pipeline reliability.
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Cost-Optimized Architecture
Implemented incremental loading, query optimization, and efficient storage strategies reducing operational expenses by 35%
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Scalable Integration Hub
Connected Google Ads, Facebook Ads, Amazon, Myntra, logistics providers, retail partners, and internal systems through standardized APIs.
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