Business Analytics

With Microsoft Fabric, a new era of data warehousing begins. The platform combines data integration, data engineering, data science, reporting, and governance within a unified cloud environment – fully managed, highly scalable, and deeply integrated with Power BI.

While traditional data warehouses often require separate systems for ETL, storage, and analytics, Microsoft Fabric consolidates these components into a single platform. All data is stored centrally in OneLake, Microsoft’s unified data storage layer, and can be accessed directly by different workloads – without complex data movement or duplication.

Microsoft Fabric unifies data engineering, data warehousing, data science, and business intelligence within an integrated cloud platform. We develop modular and scalable solutions that consolidate data from diverse sources, transform it, and make it available for analytics and reporting.

Our focus is on technical implementation – from data lakehouse architecture and automated data pipelines to Power BI reporting and machine learning integration.

Comeli wearing a lab coat and safety goggles, holding a test tube and a flask with colored liquid – symbolic representation of data science and business analytics with Microsoft Fabric.

Data Lakehouse Development

Schematic illustration of two tables merged into a unified structure – visualization of a data lakehouse architecture in Microsoft Fabric.

We design modern lakehouse architectures that combine the advantages of data lakes and data warehouses. Using Fabric’s OneLake and Synapse Data Engineering, we establish a unified platform for structured and unstructured data.

Technologies and Services:

  • Implementation of data lakehouse architectures using Microsoft Fabric OneLake
  • Development of data models with Synapse Data Warehouse
  • Creation and orchestration of pipelines with Data Factory
  • Integration of Delta tables, Parquet files, and SQL endpoints
  • Automated data loading and transformation processes using Python and SQL
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Data Integration

Several interlocking puzzle pieces – symbolizing data integration and the consolidation of heterogeneous data sources within a business analytics platform.

Modern data warehouse architectures require more than storage and data models – they depend on reliable, automated, and scalable data integration.

Microsoft Fabric provides a fully integrated platform that combines data engineering, ETL/ELT, orchestration, and analytics.

We support organizations in leveraging this new generation of data integration:

  • Fabric Data Factory for visual, low-code orchestration
  • Python and Spark notebooks for flexible and high-performance transformations
  • Pipelines, Dataflows Gen2, and lakehouse integration for consistent and reliable processes
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Analytical Reporting

Comeli wearing a tie in front of a presentation board with charts and a tablet – representation of analytical reporting and Power BI dashboards in a business analytics context.

We develop integrated reporting and analytics environments based on Power BI and Fabric Dataflows. This approach combines the strengths of a centralized data platform with flexible visualization capabilities.

Technologies and Services:

  • Data preparation using Dataflows and Data Factory
  • Development of semantic models and datasets for Power BI
  • Creation of interactive dashboards and reports
  • Automated data refresh and monitoring of data sources
  • Integration of Python and R scripts for advanced analytics
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Project Examples and Use Cases

Banking and Insurance

Illustration of a red carpet with floating paragraph symbols above it – representing regulatory financial and reporting data in the banking sector.

Objective: Consolidation and automation of complex data landscapes

Banks and insurance companies often operate with heterogeneous systems – core banking or policy systems, CRM platforms, risk modeling tools, regulatory systems, and external market data feeds.

With Microsoft Fabric Data Factory, these data sources can be centrally integrated and automated.

Typical Projects:

  • Consolidation of customer data from core banking systems, CRM, and digital channels
  • Automated calculation of risk indicators using Data Factory pipelines
  • Regulatory reporting (e.g., EBA, FINMA, Solvency II data feeds) with integration into Power BI
  • Establishment of a centralized data lakehouse for data science and machine learning

Logistics and Transportation

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Objective: Transparent supply chains and real-time operational analytics

In logistics, data originates from numerous sources – GPS tracking, transportation management systems, warehouse management, sensors, and external service providers.

Using Fabric pipelines and Spark, these datasets can be integrated and analyzed in near real time.

Typical Projects:

  • Integration of shipment and telematics data within a centralized lakehouse
  • Real-time supply chain monitoring using Power BI dashboards
  • Delivery time and capacity forecasting using Python and Spark analytics
  • Automated data preparation for CO₂ reporting and sustainability metrics

Retail and E-Commerce

Illustration of a cloud with surrounding rings – symbolizing connected trade data and cloud-based analytics platforms in e-commerce.

Objective: Data-driven decision-making in procurement, sales, and marketing

Retail environments generate data from various sources – POS systems, online shops, inventory management systems, campaign tools, and social media platforms.

Microsoft Fabric enables a unified view of these datasets, forming the foundation for automated analytics and forecasting.

Typical Projects:

  • Integration of sales and inventory data from physical stores, web shops, and supplier portals
  • Daily updates of revenue and margin reports in Power BI
  • Customer and basket analysis using Python and Spark
  • Automated campaign tracking and performance reporting