Success stories
Predictive and recommendation engine based on Machine Learning
Artificial Intelligence Project
Python, Machine Learning, APIs, analytics integration
Customer:
Tourism / Retail
Challenge
Solution
Results
Identify behavioral patterns and anticipate purchasing decisions to optimize commercial actions.
Development of Machine Learning models integrated into operational processes and analytical dashboards.
Improved conversion rates, more efficient campaigns, and decisions based on prediction rather than just historical data.
Report automation with generative AI
Artificial Intelligence Project
Azure Functions, Python, .NET, Generative AI Models (LLM), Power BI
Customer:
Education/Services
Challenge
Solution
Results
Reduce the time spent on manually writing reports and ensure consistency and quality in the content.
Implementation of a system based on generative AI that creates customized reports from structured data and free text.
Significant time savings, standardization of language, and improvement of the end-user experience.
Corporate analytical model and roadmap towards Microsoft Fabric
Power BI, semantic modeling, Microsoft Fabric roadmap
Customer:
Food Retail / Distribution
Challenge
Solution
Results
Integrate large volumes of data from ERP, sales, e-commerce, and logistics while maintaining performance and governance.
Design of an optimized semantic analytical model and definition of a clear roadmap towards a Lakehouse architecture in Fabric.
Better analytical performance, greater scalability, and a platform ready for data growth.
BI architecture and readiness for Microsoft Fabric
Power BI, Dataflows L1/L2, Microsoft Fabric, OneLake, Lakehouse, DAX governance
Customer:
Premium automotive / Distribution networks
Challenge
Solution
Results
Standardize KPIs and data models in a complex BI environment and prepare the organization for a technological leap to Fabric.
Definition of the corporate BI framework, governance of the semantic model, and design of the target architecture in Microsoft Fabric.
Robust analytical model, homogeneous KPIs, and planned migration to Fabric without impact on the business.
Comprehensive analytics platform in Microsoft Fabric
Microsoft Fabric (OneLake, Data Pipelines, Dataflows, Notebooks), Power BI
Customer:
Professional services / Architecture
Challenge
Solution
Results
Unify information from multiple internal systems and have a global view of sales, operations and finance.
Full implementation of Microsoft Fabric as an enterprise analytics platform, with automated ingestion, unified model, and executive dashboards.
End-to-end business visibility and a ready foundation for incorporating AI and document analytics.
Analytical repository of reservations in Microsoft Fabric
Microsoft Fabric (Dataflows Gen2, OneLake), Power BI
Customer:
Culture / Museums
Challenge
Solution
Results
To have consolidated and reliable information on bookings, attendance and prices from external sources via API.
Daily data extraction, consolidation in OneLake and definition of key KPIs using an analytical model in Fabric.
Greater control over activity, analysis of visit patterns, and support for pricing and planning decisions.
Analytical migration and modernization with Microsoft Fabric
Microsoft Fabric (Lakehouse, Warehouse), OneLake, Power BI, Python Notebooks
Customer:
Hospitality
Challenge
Solution
Results
Modernize the existing analytics platform and scale operational and energy data analysis for multiple hotels and user profiles.
Ingestion and consolidation of PMS, operations and energy data in OneLake, with development of governed tactical and corporate dashboards.
Unified analytics platform, reduction of information silos and improvement in operational and strategic decision-making.
Enterprise analytics platform on Microsoft Fabric
Microsoft Fabric, OneLake, Lakehouse, Power BI
Customer:
Pharma / Manufacturing
Challenge
Solution
Results
Consolidate scattered operational and financial data and create a scalable, governed corporate analytics foundation ready for advanced use cases.
Design and implementation of a Lakehouse architecture on Microsoft Fabric, centralizing information in OneLake and defining a corporate analytical model.
Unique business vision, improved data governance, and a solid foundation for evolution towards advanced analytics and AI.