One of Türkiye's leading travel and retail companies consulted with our team to design and implement a modern Data Lakehouse (DLH) architecture on Microsoft Fabric. The objective was to unify and standardize operational data across multiple countries, ensuring that business units could access consistent and real-time insights through self-service analytics. Our team architected an end-to-end solution that integrated sales, stock, and supplier data into a centralized Fabric environment. Using a combination of Azure Data Factory (ADF), Power Query, and Python-based ETL pipelines, we built a dynamic data integration layer that automates ingestion, transformation, and synchronization across various on-prem or cloud based data sources. By leveraging the complete Microsoft ecosystem, we delivered a scalable, secure, and high-performing data platform that empowers operational teams to make faster, data-driven decisions.
What we did
We designed and implemented a modern Data Lakehouse architecture on Microsoft Fabric. Within the scope of the project, we carried out Data Lakehouse (DLH) architecture setup, ETL development and data standardization, self-service analytics infrastructure development, and Power BI reporting work. Key Features: Unified Data Foundation: Standardized multi-country data models ensuring consistency across operational regions. Automated ETL Pipelines: Flexible and hybrid ETL framework combining ADF, Power Query, and Python for efficient extraction, transformation, and loading processes. Self-Service Reporting: Business users empowered with Power BI dashboards for real-time operational and strategic insights. End-to-End Integration: Comprehensive visibility across sales, stock, and procurement workflows. Scalable Cloud Architecture: Built entirely on Microsoft Fabric, optimized for performance, governance, and scalability. Governed Data Access: Role-based security and centralized data management ensuring reliability. Technology Used: The project was built within the Microsoft ecosystem, leveraging Fabric's Data Lakehouse as the unified analytical backbone. A hybrid ETL architecture was implemented using Azure Data Factory for pipeline orchestration, Power Query for model-level transformations, and Python for advanced data processing tasks. The reporting layer was developed with Power BI, enabling interactive analytics and self-service exploration across departments. This Fabric-based DLH infrastructure now serves as a single source of truth, streamlining data operations and empowering teams to make rapid, insight-driven business decisions.