Concepts and use of data

EWA Analytics makes the data collected in EWA available for analysis, reporting and integrations, without putting load on the EWA database. It consists of two services that work together:

• Analytics Data Processing copies data from the EWA database into a separate Analytics database, and transforms it into data sets that are ready for analysis.
• Analytics API gives access to those data sets through GraphQL endpoints. Reports in EWA Insight, such as the Main Report, also get their data from Analytics API.

We recommend that all data access and integrations go through Analytics API, not directly against the Analytics database.

Data sets

The data is organized in layers. Choose the layer that best matches your needs and technical resources.

Clean: foundational data sets

Who is this for? Organizations with data engineering teams that want full control, and want to build their own models, integrations or analyses.

What you get: High-quality, standardized, validated data that is still close to the source. Duplicates and formatting inconsistencies are handled, so your team can start transforming the data right away.

Key benefits:

• Maximum flexibility: transform and model the data exactly as you need it.
• Complete coverage: access to all data points available from EWA.
• Clean foundation: no time spent on basic data quality issues, such as duplicates or formatting inconsistencies.
• Custom analytics: well suited for machine learning, predictive analytics and specialized reporting.

Best suited for:

• Customers with dedicated data engineering resources
• Customers building their own models, such as machine learning or predictive analytics
• Research institutions studying emergency medical services

Technical requirements:

• Data engineering expertise for transformations and modeling
• Analytics infrastructure to process and store the data
• Understanding of healthcare data structures and relationships

Core: BI-ready data sets

Who is this for? Organizations that want to start analyzing and reporting without data engineering work.

What you get: Tables built for reporting, structured as dimensional models (fact and dimension tables) that work well with BI tools such as Power BI, Tableau and Qlik. Core only contains completed records. Records that are still ongoing or were aborted are only in Clean, so counts in Core can be lower than in Clean.

Key benefits:

• Immediate insights: start analyzing and reporting right away.
• Fast queries: the tables are structured for reporting, so BI tools can query them efficiently.
• BI tool compatibility: works with Power BI, Tableau, Qlik and similar tools, through Analytics API.

Best suited for:

• Customers without dedicated data engineering resources
• Customers that want easy access to BI-ready data

Technical requirements:

• Basic familiarity with business intelligence tools
• Understanding of healthcare data
• No specialized data engineering skills needed

Serve: ready-made data sets

Who is this for? Organizations that want a specific, ready-made answer rather than general data sets.

What you get: Data shaped for one purpose, such as a report or an integration, available only through Analytics API.

Working with the data

info

• Data is not live. Analytics Data Processing copies new data on a schedule, by default every 60 minutes. Data in the API can therefore be up to one interval old, plus the time a run takes.
• All timestamps are in UTC. Convert them to local time in your reports.
• Deleted records are kept in the Clean layer. Rows deleted in EWA stay in the Clean tables, with the time of deletion in deleted_at. Filter on an empty deleted_at to leave them out.

Where to find what

• The tables in Clean and Core are described per version under Data Processing.
• How to query the data, and what the Serve endpoint offers, is described under API.
• Which versions work together is listed in Version Compatibility.
• How to install, configure and upgrade both services is described in Installation.

Architecture