Analysis and Reporting with Orchestral
Healthcare organizations generate huge volumes of data, but too often it remains siloed, underutilized, or difficult to analyze. Orchestral addresses this challenge by embedding reporting and analysis directly into its health intelligence platform. With pre-built Jupyter Notebooks, a secure JupyterHub environment, and ready-to-use dashboards, Orchestral ensures that insights are available from day one. These tools not only provide immediate visibility but also allow for customization and advanced analytics as needs evolve.
Features and functions
Pre-built Jupyter Notebooks – ready-to-run notebooks designed for healthcare use cases, available through a centrally managed JupyterHub. They provide standardized queries, workflows, and visualizations for quick analysis.
Dashboards – three pre-built dashboards deliver instant oversight:
Data quality dashboard – tracks validation failures, warnings, and ingestion errors.
Data traffic dashboard – monitors arrival patterns, volumes, and anomalies in real time.
Data processing dashboard – provides visibility of data flow through ingestion, transformation, and output.
Custom reporting – lightweight but powerful support for building new Jupyter Notebook jobs that generate processed datasets. These can be scheduled, versioned, and used in custom dashboards or shared externally.
How it works
Orchestral’s reporting and analysis functions are built on top of its Health Data Model and Data Lake. Analysts and researchers access data through Jupyter Notebooks within the secure governance boundary, eliminating the risks associated with data exports. Each notebook is version-controlled, ensuring repeatability and transparency.
Dashboards are automatically populated from ingested and processed data, with configurable parameters for environment and time period. Processed datasets generated from notebooks or jobs are stored back into the Data Lake, where they can be reused for further analysis or accessed by external BI tools such as Tableau or Power BI.
This combination of pre-built assets and extensible tooling gives organizations both immediate value and long-term flexibility.
Use cases
Operational monitoring – track data arrival patterns, processing errors, and system performance in real time.
Data quality management – identify structural issues, non-fatal warnings, and fatal ingestion errors, with clear reporting for data stewards.
Performance benchmarking – compare outcomes across sites, providers, or cohorts with standardized metrics.
Regulatory and sector reporting – deliver mandated reports in required formats without additional development.
Advanced research – combine clinical, claims, and social determinants of health data into custom datasets for research and model training.
Benefits
By delivering pre-built notebooks and dashboards, Orchestral drastically reduces the “time-to-insight” gap. Instead of spending months building monitoring tools or pipelines, teams have access to healthcare-ready assets from day one.
Key benefits include:
Faster decision-making – immediate access to reliable dashboards and notebooks.
Improved data quality – continuous visibility of validation errors and anomalies.
Flexible customization – ability to extend with new jobs, datasets, and dashboards as organizational needs evolve.
Trusted governance – all reporting and analysis happens within the secure boundary, ensuring compliance with patient privacy requirements.
Actionable intelligence – supports operational monitoring, strategic planning, and advanced research, all from the same platform.
Ultimately, Orchestral empowers healthcare leaders to spend less time wrangling data and more time acting on insights that improve patient outcomes and system performance.