Intelligent Data Solutions
We design and implement modern data architectures, Business Intelligence solutions, and machine learning-ready pipelines so that your data can compound value across analytics, decisions, and AI.
DataCompound is a boutique data & AI practice led by Diogo Souza, a data engineer with nearly 15 years of experience across aviation, finance, government, and infrastructure. We specialize in bridging Business Intelligence and Machine Learning so analytics and AI grow on the same solid foundation.
Rather than chasing isolated dashboards or one-off models, we help you build a compound data foundation: layered architectures (ODS 路 DWH 路 marts 路 semantic models) that serve reporting, self-service analytics, and ML workloads consistently.
We partner with organizations that want to move from legacy reporting to AI-ready data ecosystems.
Design and build robust data models and architectures, including operational data stores, warehouses, marts, and lakehouse patterns aligned with your business domains.
End-to-end BI solutions: ingestion, transformation, curated marts and semantic models, plus interactive dashboards used by safety, operations, engineering, and leadership teams.
Preparation of AI-ready datasets and features, and integration between BI and ML workflows for forecasting, anomaly detection, and risk scoring.
A sample of initiatives that reflect our approach to AI-driven Business Intelligence. Detailed case studies are available on request.
Unified events, investigations, and audits in a dimensional model powering safety and compliance analytics for multiple stakeholder groups.
Tech: SQL Server 路 Databricks 路 Delta Lake 路 Power BI
Semantic models and dashboards that let teams explore incidents, risk ratings, audit findings and KPIs without manual exports or duplicated logic.
Tech: Power BI 路 QlikView 路 Tabular models
Curated datasets and feature pipelines supporting demand forecasting, anomaly detection and risk scoring, built on top of an existing BI foundation.
Tech: Python 路 Databricks 路 ML libraries
We work with modern cloud-native platforms, with a strong focus on Azure, Databricks, and the modern BI ecosystem.
Azure 路 Databricks 路 Delta Lake 路 SQL Server 路 Lakehouse & DWH
Power BI 路 QlikView 路 semantic modeling 路 metrics layers
Python 路 ML/AI libraries 路 feature design 路 ML-BI integration
Planning a new data platform, modernizing legacy BI, or preparing for AI initiatives? DataCompound can help you design a pragmatic roadmap and build the foundations that last.