Enterprise ETL Management & Data Analytics
ETL management using Azure Data Factory and .NET Core APIs for seamless data integration across multiple sources — with Power BI dashboards for real-time insight.
- .NET Core 6.0
- Azure Data Factory
- Power BI
- Azure Functions
- SQL Server
- Industry
- Data analytics
- Service
- Data engineering & BI
- Platform
- .NET Core 6.0 + Azure
- Dashboards
- Power BI & Power Apps
Seamless data integration across every source
This project focuses on ETL (Extract, Transform, Load) management using Azure Data Factory (ADF) and .NET Core APIs, enabling seamless data integration across multiple sources. It involves webhooks, Google BigQuery, and warehouse storage export jobs to streamline data processing.
The primary goal is to help clients analyze data efficiently and make data-driven decisions using Power BI dashboards and Power Apps. The system automates data extraction, transformation, and loading, ensuring real-time insights for business intelligence.
From scattered data to real-time insight
The challenge
- Data lived in multiple sources, including webhooks and Google BigQuery.
- Extraction, transformation and loading needed to run without manual effort.
- Clients needed to analyze data efficiently and make data-driven decisions.
Our solution
- Automated ETL pipelines with Azure Data Factory and .NET Core 6.0 APIs.
- Event-driven Azure microservices — Logic Apps and Functions — for scalable processing.
- Azure Analysis Service tabular models with DAX calculations and row-level security.
- Power BI dashboards and Power Apps on top of the warehouse.
The result
- Real-time insights for business intelligence.
- Scalable, fault-tolerant processing with cost optimization.
- Real-time data refresh in analytics models.
End-to-end ETL and analytics
Automated ETL pipelines
Extraction, transformation and loading automated with Azure Data Factory.
Real-time processing
Real-time data processing and transformation.
Interactive Power BI dashboards
Dashboards and Power Apps for data-driven decisions.
Webhook integration
Webhooks deliver real-time updates into the pipeline.
Google BigQuery integration
BigQuery connected as a source alongside other systems.
Warehouse export automation
Warehouse storage export jobs run automatically.
Technology stack
Backend development
- .NET Core 6.0 APIData APIs
- Entity FrameworkData access
- LINQData queries
- SQL ServerDatabase
- Azure DevOpsCI/CD
Azure services
- Azure Data FactoryETL pipelines
- Azure Logic AppsWorkflows
- Azure FunctionsServerless
- Azure API ManagementAPI gateway
- Azure Web ServicesHosting
Data & analytics
- Power BIDashboards
- Power AppsBusiness apps
- Google BigQueryData source
- Data warehouseStorage exports
Advanced modeling and scalable processing
Azure Analysis Service
Successfully implemented Azure Analysis Service for advanced data modeling and analytics capabilities.
- Tabular data models
- DAX calculations
- Row-level security
- Real-time data refresh
Microservices architecture
Implemented Azure microservices including Azure Logic Apps and Azure Functions for scalable data processing.
- Event-driven architecture
- Scalable processing
- Fault tolerance
- Cost optimization
What our team delivered
Project excellence
- Managed project quality and consistency
- Ensured timely delivery
- Coordinated with stakeholders
- Resource allocation and planning
- Risk management and mitigation
Technical innovation
- Designed and developed backend components
- Implemented automated testing
- Managed Azure DevOps deployment
- Created comprehensive documentation
- Performance optimization
Need reliable data pipelines and dashboards?
Let's discuss how automated ETL on Azure and Power BI can give your team real-time insight.