Data Engineering for a Multi-Brand Retailer
A unified cloud data pipeline designed to process and transform large ERP datasets into powerful business insights.
Industry
Retail
Overview
Services Provided
A leading retail enterprise needed a powerful cloud data engineering solution to process, transform, and visualize data coming from multiple on-premise ERPs and OMS systems.
The goal was to build a robust, scalable data pipeline that automates data curation, transformation, and enrichment for real-time business reporting.
8 months
June 2021
Data Engineering
Custom Data Pipeline Architecture
Services Provided
The Goal
Develop a cloud-based data engineering solution that seamlessly processes 850+ GB of ERP data daily.
Unified Processing
Design a single data architecture to manage ingestion, curation, and transformation from multiple ERP and OMS systems.
Business-Ready Insights
Enable Power BI dashboards powered by standardized and enriched data elements for faster decision-making.
Scalability
Sync
Data
Flows
Challenges
Massive Data Volume
Processing 850+ GB daily from multiple sources while ensuring accuracy and timeliness was a significant challenge.
Complex Data Transformation
Each ERP had unique business rules, requiring a flexible yet consistent data transformation model.
Latency
Logic
Failures
Gaps
Process
DetermineWe start by understanding your needs, challenges, and assumptions to lay a strong foundation for your project. This ensures a smooth ecommerce website development services journey.
STEP 1
STEP 2
DescribeFrom project scope to risk assessment and milestones, we map out every detail, creating a clear roadmap as a leading ecommerce development agency for seamless execution.
DesignWith wireframes, prototypes, and a user-centric approach, we craft intuitive UI/UX and robust system architecture, enhancing your store with best ecommerce hosting services.
STEP 3
STEP 4
DevelopEngineering, API integrations, QA, and security come together to build a high-performing, secure, and scalable solution with expert Ecommerce web development.
DeployFrom environment setup to product deployment and migration, we ensure a smooth launch with ongoing support, backed by reliable best ecommerce hosting services.
STEP 5
Solution
We implemented a cloud-native data engineering architecture built on Azure to handle large data volumes efficiently and reliably.
Data Ingestion
Data Ingestion
Problem:
On-premises ERP data wasn’t easily accessible or timely.
Solution:
Built automated dataflows using Azure Data Factory and Integration Runtime to sync ERP data to Azure SQL Servers daily.
Data Curation
Data Curation
Problem:
Each ERP had unique structures and rules.
Solution:
Used Azure Data Bricks and Python for customized curation, applying business logic tailored to each ERP.
Data Transformation
Data Transformation
Problem:
Consolidating curated data into a unified model was complex.
Solution:
Transformed and standardized all curated data into a common schema, enabling consistency and easy consumption across systems.
Data Enrichment & Visualization
Data Enrichment & Visualization
Problem:
Fragmented outputs made reporting inefficient.
Solution:
Combined curated datasets into 17 enriched Data Elements used directly by Power BI for dynamic dashboards and reports.
DevOps Automation
DevOps Automation
Problem:
Manual deployment slowed delivery.
Solution:
Adopted Azure DevOps pipelines and Kubernetes orchestration to automate versioning, deployment, and monitoring.
Technologies used
Azure Databricks
Scalable platform for data processing.
Azure Data Factory
Automated pipelines for data workflows.
Python
Scripting and data processing language.
Data Lake
Central storage for all data.
MSSQL
Secure and scalable database engine.
Kubernetes
Orchestration for containerized workloads.
Azure DevOps
End-to-end CI/CD and collaboration.
850+ +
GB of
data processed daily
16+ +
curated Data
Elements powering dashboards
70% +
faster report
generation
Impact
Reliable Data Infrastructure
The client now operates on a stable, scalable cloud pipeline capable of handling massive data volumes daily.
Unified Insights
Power BI dashboards provide consistent and accurate business intelligence drawn from standardized, enriched datasets.
Operational Efficiency
The automation and orchestration reduced manual data handling, freeing teams to focus on analysis rather than processing.
Scalability & Flexibility
The system supports adding new ERPs and data elements with minimal configuration and no downtime.
Faster Decision-Making
Executives gained access to real-time analytics, driving faster and more confident business decisions across regions.
Conclusion
A unified, cloud-native data engineering framework that powers real-time insights and smarter decisions.
Data-Driven Growth
The client’s analytics capabilities improved drastically, driving better forecasting and performance visibility.
Future Expansion
With a scalable cloud backbone in place, the platform is ready to integrate new data sources and expand reporting dimensions effortlessly.
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