Client
Neemans
Overview
The project focused on building a robust ETL pipeline to handle large volumes of sales, inventory, and customer data. Using Azure Data Factory, SQL, and cloud storage, I created an efficient system that automates data extraction, transformation, and loading for real-time insights.
Client
Neemans
Service
ETL Automation
Cloud-Based Data Pipeline
Azure Integration
Content
The Challenge
The key challenges included handling diverse data sources, ensuring real-time processing, and maintaining data accuracy. Additionally, the pipeline needed to be scalable, cost-effective, and optimized for performance
The Solution
I designed a cloud-based ETL solution using Azure Data Factory, Azure SQL Database, and Blob Storage, ensuring seamless data ingestion, transformation, and analysis. Automated workflows and error-handling mechanisms were implemented to maintain data integrity and reliability
The Result
The Azure-based data pipeline significantly improved data accessibility, processing efficiency, and reporting accuracy. This helped Neemans make data-driven decisions faster, enhancing their e-commerce operations and customer insights.
