Case study · Healthcare

From manual reports to a real-time healthcare platform.

How Tenplus turned siloed Kipu and Dazos EMR data into a real-time healthcare analytics platform for a growing addiction-treatment provider.

Azure Data FactoryAzure FunctionsDatabricksDelta LakePower BI

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Days → real timeData freshness

0Manual exports

1Source of truth

Client background

A multi-clinic addiction-treatment provider.

The client is a growing healthcare organisation focused on addiction treatment across multiple clinics. Both core systems were essential, but their data lived in separate silos, so reporting across them was slow, manual and hard to trust.

At a glance

Kipu for EMR and clinical workflows
Dazos for operations, scheduling and ancillary data
Good systems, but no unified data layer to connect them

The problem

Manual, delayed and siloed reporting.

The organisation had good systems, but no unified data layer, so every team worked from its own numbers.

Data from Kipu and Dazos was exported manually from web interfaces.

Reports were often days out of date by the time leadership saw them.

Every department used its own spreadsheets, leading to conflicting numbers.

Leaders had no single view of patients, clinics or provider performance.

No real-time reporting, which limited fast decision-making.

What they needed

Centralised, near real-time data
Automated pipelines
High data quality with full audit trails
A self-service reporting layer for clinicians and operations

Solution overview

A cloud-native analytics platform on Azure and Databricks.

Tenplus designed a solution using Azure Data Factory, Azure Functions and Databricks, with Power BI as the reporting layer.

ADF pipelines

pulled data from Kipu and Dazos APIs using token-authenticated, paginated calls.

Raw JSON

landed in a controlled storage layer for full traceability.

Azure Functions

cleaned and normalised the data into analytics-ready tables.

Databricks notebooks

applied business logic, enrichment, deduplication and Delta Lake optimisation.

Curated Delta tables

powered Power BI dashboards for real-time self-service analytics.

Monitoring & alerts

used ADF logging, Log Analytics and Microsoft Teams notifications.

Built with Azure Data FactoryAzure FunctionsDatabricksDelta LakePower BI

How we built it

Five steps from ingestion to insight.

Step 1Ingesting Kipu and Dazos data with Azure Data Factory

Step 2Cleaning and normalising data with Azure Functions

Step 3Business logic and transformations in Databricks

Step 4Monitoring, logging and alerting

Step 5Real-time analytics with Power BI

Results

From manual reports to always-on insights.

Eliminated manual exports from Kipu and Dazos.
Improved data freshness from days to near real time.
Created a single source of truth for clinical and operational reporting.
Reduced errors and rework from spreadsheet-based reporting.
Enabled self-service analytics for clinicians and operations staff.
Built a scalable foundation ready for more systems and use cases.

★★★★★

Before working with Tenplus, our reporting process was slow, manual and full of gaps. Now we have a real-time data platform that pulls clean, trusted data from both Kipu and Dazos without our team lifting a finger. Our clinicians and operations teams depend on the dashboards every single day. Tenplus gave us clarity, speed and a system that will support our growth for years. It has changed how we make decisions.

Healthcare organisation · Addiction treatment provider

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