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How 33N Enabled Real-Time NHS Data Visualisation

A small team of clinicians and data scientists wanted to make UK NHS hospitals more efficient with Tableau visuals—so they partnered with OSO’s cloud architecture and big data experts


months to be GPG 13 compliant


minutes MTTR for Tableau Server redacted to


day to onboard new NHS sites, taking hours rather than days


When OSO stepped in, we got our AWS strategy done better, faster, and with more depth and breadth than we could have ever done on our own.

Kavin Abelak CTO | 33N

Explore how AWS support helped 33N successfully enable real-time data visualisation at the NHS

How did we enable real-time data visualisation?

  • Redesigned 33N’s systems to create GPG13-compliant cloud architecture
  • Migrated data to Amazon’s AWS Relational Database Service (RDS)
  • Integrated Epic and Tableau to provide real-time NHS data visuals

Healthcare isn’t immune to innovation.

This year, 33N—a small team of clinicians and data scientists—wanted to change workflow modeling inside UK hospitals. With OSO’s help, it created a product that transforms NHS Hospital Episode Data (HES) into clear, coherent, and accessible visuals.

According to the NHS, HES data helps hospitals:

  • Monitor critical trends and patterns in data
  • Plan their services for the future
  • Assess the quality of hospital care

Cheers for automated Tableau deployment! With careful iteration and implementation, we provided 33N with a tool that will make it easier for hospitals to identify inefficient systems, shorten waiting times, and improve the quality of care for sick patients.

The Company: 33N

First, some background. Fundamentally, 33N is an organisation that believes in high-quality healthcare. To help frontline healthcare workers make informed, intelligent decisions, the team:

Provides data visuals of patient-doctor data.

Collects HES data, refines and cleans datasets, provides visuals, and equips healthcare workers with a tool to improve how they interact with patients.

Develops plans to improve hospital systems

Defines the scope of the problem, establishes hospital baselines, links datasets for insights, models data, and improves operational efficiency.

OSO loved 33N’s mission, so we partnered up to help them use big data sources and cloud architecture. We redesigned 33N’s architecture, integrated visual data platform Tableau and NHS’s e-record system Epic, and made it possible for clinicians to visualise HES data in real time. Here’s how we started using Tableau.

real-time data visualisation photo

The Challenge ❌

When a child, parent, or partner is sick or injured, nothing’s more important than getting them the best care in the world.

Before OSO got involved, 33N had big dreams of tackling healthcare challenges across the UK. Even though Brits are lucky to have some of the best healthcare in the world, hospitals still struggled to streamline their systems.

To start fixing this problem, 33N’s team wanted to introduce machine learning to deliver safe, effective improvements for patients and staff across a range of hospitals. A Tableau server was the natural answer, but 33N’s team lacked cloud architecture and big data expertise—in short, they had no way to implement their vision.

The Solution 😊

First, OSO assessed 33N’s existing AWS architecture based on the five pillars of Amazon’s Well Architected Framework: operations, security, reliability, performance, and cost (StormForge, 2021). What could we create that would help them improve their configuration?

5 pillars of the AWS well-architected framework with icons

Right away, we determined that 33N needed Amazon EC2, AWS ALB, and Auto Scaling to make its systems more resilient and help balance its application load.

We wanted to establish a repeatable and scalable blueprint for deploying Server at scale in AWS. To achieve that blueprint, OSO provided 33N with a framework of repeatable infrastructure that could be modified to meet top-notch security protocols.

33N wanted a Tableau Server environment that ran on AWS. However, they also wanted 33N’s enterprise active directory involved so that they could have better user access and integrate it with existing data sources.

We proposed a solution that ensured that 33N’s platform’s quality and efficiency would be monitored, scalable, and secure, serving as a blueprint for their subsequent Tableau deployments on AWS.

To do so, we productionised each bit of 33N’s architecture for redundancy and high-availability.

We applied best practices for backup and restore, meeting the RPO and RTO requirements.

What’s more, we provided a consistent approach for other teams to make use of the Tableau solution. We wanted 33N to be able to take a self-service approach and feel confident about their AWS solution.

Finally, OSO provided the 33N Cloud Platform team with a highly-scalable, secure, fully-automated, cloud-native Tableau deployment on AWS.

Our Tableau Deployment Library offered 33N’s developers an easy-to-use experience, while empowering data teams with the autonomy and control they needed to make sure their models were accurate.

In addition, we made the source code available so that 33N’s developers could debug, customise, and modify the solution to fit their future needs.

Simply put, we provided 33N with a copy of our Tableau Deployment Library—plus, we worked with them to establish added features!

  • Data encryption
  • Secrets management
  • Instance and network isolation

We configured AWS CloudTrail, Amazon CloudWatch, and AWS Guardduty so that 33N could log and monitor resources in their AWS environment. By adding these logs to EKK (Elasticsearch, Kineses, and Kibana), 33N could suddenly visualise activity over its entire account.

As a result, 33N could feel secure using their AWS environment, including HES data sources. If anyone tried to connect or control their applications, BAM—they’d be alerted in a flash.

What Services Did OSO Deliver?

Here’s a more in-depth look at the tools we configured:

Cloud Architecture
  • Amazon Virtual Private Cloud (VPC) & VPC Peering – Launched AWS resources into a virtual environment and helped migrate data between different VPCs. 
  • VPN – Installed an OpenVPN equipped with CIS security, configured for high availability (HA) to avoid downtime and including Amazon Relationship Database Service (RDS) credentials. 
  • Amazon RDS – Set up and scabale a cloud multi-region encrypted MySQL database, making it easy for 33N to scale its visualisations as needed, provide ultra-fast service, and ensure its applications stored data in a stable and constantly-accessible form. 
  • Amazon Elastic Compute Cloud (EC2), Application Load Balancer (ALB), and Autoscale – Provided secure, easy, web-scale cloud computing, helped balance loads across multiple servers, and ensured that Auto Scaling AWS would automatically adjust compute resources to keep 33N’s apps running smoothly.
Automation-First Systems
  • HashiCorp TerraformAutomated 33N’s AWS infrastructure, including its applications, network, and security definitions. Provided re-use and automated pipelines to deploy infrastructure. 
  • Amazon Route 53 – Easily routed the clinic end user(s) to 33N’s web applications to (a) connect their requests to 33N’s new AWS infrastructure and (b) manage top-level domains and subdomains.
Data Storage and Security
  • Amazon Simple Storage Service (S3) – Uploaded 33N’s static content (images, stylesheets, artefacts, and configurations) into an S3 bucket, helping 33N perform secure batch processing
  • Amazon Simple Notification Services (SNS) – Allowed 33N to send messages and notifications directly to clinic users with SMS text messages, courtesy of a single endpoint.
  • Amazon Key Management Service – Added the ability for hospitals to create and manage cryptographic keys with EBS root volume encryption. GPG13 compliance!
Compliance and Risk
  • AWS CloudTrail – Allowed 33N to perform operational audits, log, and monitor across its entire AWS infrastructure, providing a good digital trail in case anything went awry.
  • Amazon CloudWatch – Provided 33N with a single overview of its AWS logs, metrics, and applications for easier testing, risk analysis, and security alerts.
Accessible Data Visualisation
  • Tableau Server – Provided the end user(s)—clinicians and frontline healthcare workers—with streamlined, targeted data visuals to help them iterate and improve their systems.

The Result 🎉

Now, the team at 33N has a modern, cloud-native platform that can grow as their operations expand, fully equipped with AWS automation and analytics.

The portal is secure—only valid employees, support staff, and contractors have access to its data—and infinitely scalable for the future.

In addition, OSO provided extra AWS tools so that 33N can detect network intrusions, scan for vulnerabilities, and rely on trusted data backup. The result? The team at 33N can now focus on their mission, confident that data sources and systems will run smoothly regardless of scale.

Together, we integrated NHS patient data with Tableau, creating custom dashboards that doctors could access, query, and filter on-demand.

‘When OSO stepped in, we got our AWS strategy done better, faster, and with more depth and breadth than we could have ever done on our own’, says Kavin Abelak, Co-founder and CTO of 33N.

Thanks Kavin! We loved collaborating on Tableau content and use cases. Keep up the critical work.

To learn more about AWS consulting, deployment of Tableau server environments and enabling real-time data visualisation, check out our services here.

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