Executive summary
As data-heavy organizations face increasing pressure to deliver tangible returns on their data investments, many find that traditional Business Intelligence (BI) tools are no longer sufficient.
This case study explores how Zelytics partnered with a rapidly growing U.S. healthcare scaleup to develop a cost-effective, scalable internal data application platform that extended beyond the capabilities of their existing BI system.
Zelytics delivered a customized solution leveraging Streamlit, integrated with the client’s Kubernetes infrastructure, to create a secure, scalable, and flexible data application platform.
This platform enabled the client to build and deploy interactive data-driven applications, meeting the increasing demand for automation and advanced analytics across business units without escalating costs.
Key outcomes included:
Enhanced Scalability and Security: Zelytics implemented a robust architecture featuring OAuth2 authentication, role-based access control, and dynamic data masking, ensuring compliance with HIPAA/HITECH regulations allow for the development of 5x more data applications*.
Streamlined Development and Deployment: The client’s technical team was empowered with custom development environments, streamlined CI/CD processes, and reusable templates, reducing the time and complexity of developing and deploying new applications by 90%*.
Optimized Performance and Cost Efficiency: By offloading caching and session management to AWS services, the solution enabled sustainable scaling of data applications while reducing resource consumption and costs by 70%*.
*Curious about how we measured these metrics? Reach out and we can provide more details to you.
In a matter of a few months, Zelytics transformed the client’s approach to data applications, delivering a solution that enhanced both operational efficiency and cost-effectiveness. This case study highlights the strategic advantage of building tailored data platforms that go beyond traditional BI capabilities.
Context & Background
Many data-heavy organizations are heavyweights in data analytics but are severely underweight in delivering a return on investment (ROI) from their data.
With the unwinding of decades of zero-interest funding, the ROI of data departments across industries is under heavy scrutiny.
The modern data stack, fueled by this environment, has driven rapid growth in business intelligence (BI) capabilities for many companies, often accompanied by rapidly increasing expenses on cloud data warehouses connected to BI platforms.
There is a growing desire for more value-added activities beyond delivering dashboards within an increasing number of organizations. An increasing number of companies are relying on in-house solutions to save millions of dollars in costs while doing so.
In this case study, we share how Zelytics developed an internal data application platform for a high-growth scaleup in the US healthcare industry.
Pain Points & Challenges
There was a lot of demand across business units to build data-driven automations for the sustainable growth of the business.
Higher management perceived any additional investments in the BI platform as yielding diminishing returns on investment.
The client had a lot of capable technical talent in-house with a diverse toolkit to build data products, but exposing these in interactive ways to end-users was a very time-consuming cross-department and cross-discipline effort.
The client was concerned about significant increases in overall costs with a larger amount of self-service use of interactive data apps, as they had observed similar trends with their BI platform.
The client had experimented with various ways to deploy data apps within their team without success and lacked fundamental traditional application expertise to build these systems.
Scope
Through multiple scoping sessions with the client, we developed the following scope for this project:
Data applications should meet at least the capabilities of the BI platform and allow for extended reporting with any Python-supported data library.
Data applications must be able to integrate with the client's existing Kubernetes clusters.
The data application platform should be simple to deploy and should primarily use technologies familiar to the engineers.
Data applications should have a robust authentication layer and role-based access control.
Data applications should have extendable components to support custom requirements and should be extendable with front-end frameworks.
The security architecture is of utmost importance, as the company handles a significant amount of PII/PHI data subject to HIPAA/HITECH protections.
Solutions
Objective: Deploy a Scalable and Secure Data Application Platform with BI+ capabilities
The first objective was to establish a scalable and secure data application platform that could match or exceed the capabilities of the existing BI tool. Zelytics identified Streamlit as the ideal platform, given its lightweight, Python-native nature, which aligns well with the client’s existing technical stack.
Within a month, Zelytics delivered templates to deploy an architecture that set up Streamlit apps on a Kubernetes cluster with a multi-level security approach, introducing the following features:
An OAuth2 authentication layer connected to a federated identity provider.
IdP group-based access to data applications.
A dynamic data masking system to control the visibility of PII/PHI based on data warehouse roles.
Objective: Enable Efficient Development and Customization of Data Applications
The next goal was to empower the client’s technical team to efficiently develop, test, and maintain custom data applications while allowing for future flexibility on both the front and back ends.
The first step Zelytics took was creating a custom repository for React components in Streamlit, enabling the development, testing, and deployment of components as stable pip packages.
Next, we set up a second repository with polished, high-quality templates for Streamlit applications.
To onboard the data team, we developed a custom development environment based on VS Code devcontainers that allowed for seamless, interactive testing of multiple front and back-end components simultaneously. Each team member was provided with this environment and received extensive training.
Finally, we set up a robust CI/CD process that automated the deployment of applications in local, staging, and production environments, utilizing strategies such as split testing and blue-green deployments.
Objective: Optimize Data Application Performance and Resource Utilization
After the successful setup of the initial data applications and testing with end users, the client wanted to expand further and requested additional improvements.
The client sought to offload caching and session management from the local resources of the Streamlit servers and the data warehouse.
Zelytics extended Streamlit’s capabilities by enabling caching and state management through AWS services, allowing the applications to scale more sustainably using S3 and ElastiCache.
Closing remarks
Are you facing similar compliance challenges in your organization? Healthcare, finance, you name it. At Zelytics, we have dedicated consultants to set up comprehensive data governance solutions for your company.
Zelytics offers a complimentary consultation to help you gain clarity around your main challenges and develop a data-driven strategy to overcome them.
Let’s talk and get to know each other and see what we can do for your business.
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