We create data-driven digital work that moves businesses forward.
Data engineeringAI & analyticsDigital productsBusiness intelligence
Our case studies
Data, research and product work designed for practical impact.
Explore how Codegner Dev applies data engineering, analytics, cloud technologies and thoughtful product design to turn complex challenges into useful, measurable outcomes.
Reliable data pipelines for confident decisions.
Annex Data Engineering turns disconnected operational data into dependable, structured datasets that teams can use for reporting, analysis and better decisions.
The challenge
Raw data loses value when it is inconsistent, difficult to validate or slow to reach the people who need it. The challenge was to establish a repeatable path from source data to trusted insight.
The work
A practical end-to-end data workflow was designed to ingest, clean and transform source records into analytics-ready tables, giving downstream teams a clearer and more reliable foundation.
Data pipelines · Transformation · Analytics infrastructure
Healthcare data built for timely monitoring.
Patient Vital Monitoring demonstrates a cloud-focused approach to preparing healthcare information for dependable analysis, monitoring and future scale.
The challenge
Patient data needs to be handled in a structured way before it can support meaningful monitoring. Fragmented records make it harder to identify patterns and provide timely visibility.
The work
The project applies modern data-engineering principles to organise patient vital information into a workflow that supports monitoring use cases and scalable analytical exploration.
GCP · Healthcare data · Monitoring · Data engineering
Financial data translated into research signals.
This J.P. Morgan quantitative research case study applies data science and financial modelling to investigate the relationships hidden within market datasets.
The challenge
Financial information is dense and fast-moving. Discovering useful relationships requires a research process that is statistically sound, repeatable and clear enough to interrogate.
The work
Python-based quantitative methods, financial analysis and machine-learning techniques were combined to explore patterns and turn complex inputs into evidence-led research.
Python · Quant finance · Machine learning · Financial data
Retail performance made visible and actionable.
Retail Sales Analytics transforms extensive sales data into a clear business-intelligence experience, helping stakeholders see performance, trends and opportunities at a glance.
The challenge
When sales information lives across large datasets and static reports, identifying what is changing—and why—takes too long for a business that needs to act quickly.
The work
An analytical reporting experience was developed to organise performance indicators, reveal product and sales trends, and make business questions easier to answer.
Power BI · Dashboards · Data analysis · Business insights
Booking data shaped into hospitality insight.
Hotel Booking Analytics explores the customer and operational patterns in hospitality data through a modern cloud analytics workflow.
The challenge
Booking records hold valuable signals about demand, customer behaviour and operational performance, but these signals are difficult to use without a consistent data model and analytical layer.
The work
A Snowflake and SQL workflow was used to model hotel-booking data, making it easier to investigate patterns, measure performance and support more informed planning.
Radiantor pairs clear product storytelling with thoughtful interface design, helping visitors understand the service quickly and move through it with ease.
The challenge
A useful digital product still needs a focused experience. Without strong hierarchy and clear language, even a valuable service can be hard for visitors to understand.
The work
The site was designed and developed as a responsive product experience, using an intentional visual system and direct content to present the service with clarity.
