Previous projects

Anonymous examples of data and technical transition work.

Client names are intentionally omitted. The point is to show the shape of the problems, the kind of work involved, and the outcomes ELFA Data is built to support.

Healthcare analytics

Turning clinical and event data into stakeholder-facing insight.

Analytics dashboard with charts and performance metrics

Built analytics workflows around healthcare events, KOL-facing insights, dashboards, and data products where accuracy, explanation, and trust mattered as much as engineering speed.

  • Cloud pipelines for large healthcare datasets
  • Analytics layer for business and domain stakeholders
  • Clearer reporting and model adoption support

SAP medical supply chain

Making ERP and supply chain data more usable.

Data pipeline flow from collection to analysis

Supported ingestion and transformation of SAP and ERP data for operational reporting, medical supply chain visibility, and more reliable downstream analytics.

  • SAP and ERP source integration
  • ETL reliability and orchestration
  • Operational reporting foundations

Automotive analytics

Forecasting, charging analytics, and repair-related prediction.

Machine learning pipeline from data collection to maintenance

Delivered forecasting and predictive analytics for automotive use cases, including electric vehicle charging availability, rescheduling recommendations, and car replacement or repair-related signals.

  • Forecasting models for platform planning
  • Recommendation and prediction workflows
  • Analytics adopted by operational stakeholders

EU and US health insurance

Data pipelines and analytics in compliance-sensitive contexts.

Worked with healthcare and insurance-related data where quality, traceability, and stakeholder communication were essential for confident decision support.

  • Cloud-native data processing
  • Decision-support analytics
  • Careful communication across business and technical teams

FinTech

Risk, fraud, and reporting quality for data-driven products.

Fraud analytics dashboard with transaction and risk metrics

Built and improved data products around fraud detection, risk signals, operational monitoring, and analytics reliability in product environments where false positives and speed mattered.

  • Fraud and risk model delivery
  • Production analytics and monitoring
  • Pipeline and reporting improvements

Confidentiality

Trust matters before, during, and after delivery.

ELFA Data keeps client details private unless there is clear permission to share them. Public examples are therefore described by industry, problem type, and outcome rather than by company name.