Data Integration with Microsoft Fabric
Data is the foundation of every analysis. However, a complete picture only emerges when information from different sources is consolidated, cleansed, and structured. With its modern platform, Microsoft Fabric provides an integrated environment to centrally bring together data from cloud, on-premises, and external systems – efficiently, securely, and at scale.
Our solutions connect business intelligence, analytics, and data science into an end-to-end data ecosystem. We combine visual tools with flexible code-based approaches – aligned to your organization’s requirements.
- Design and implementation of integration processes in Microsoft Fabric
- Development and automation of Data Factory pipelines
- Spark-based data processing using Python or R
- Implementation of scalable dataflows between data lakehouse, warehouse, and reporting
- Workshops and training for data engineers and analysts
Data Factory in Microsoft Fabric
With Data Factory in Microsoft Fabric, data flows can be designed in a clear and structured way. The drag-and-drop interface makes it easy to connect data from various sources – such as SQL databases, cloud storage, or web APIs – transform it, and load it automatically.
Highlights:
- Intuitive low-code interface for data pipelines
- Support for a wide range of connectors (SQL Server, Azure, SAP, Oracle, and more)
- Automated workflows for loading and cleansing processes
- Monitoring and logging directly within the Fabric environment
Python & Spark in Microsoft Fabric
For more complex scenarios, Microsoft Fabric provides a fully integrated Spark environment. Data engineers and data scientists can work with Python, SQL, R, or Scala to develop custom integration and transformation processes.
Highlights:
- Use of Apache Spark directly in Fabric notebooks
- Support for Python libraries (e.g., pandas, pyspark, numpy)
- Direct access to OneLake data – without duplicates
- Combination of automated pipelines and code-based transformations