Modernize Data Platform in HealthTech
aidhere is a market leader in digital health applications for the holistic treatment of diseases. To help people live healthier life, the aidhere team consistently seeks out solutions that seamlessly blend into the daily routines of their users.
To enable the creation of such practical scenarios, we have constructed a highly adaptable data platform that can scale dynamically, spans across multiple compute locations, and guarantees reliability.
​
Technologies: Open Telecom Cloud (OTC), Airflow, dbt, Metabase, Kubernetes, Docker, Terraform, dlt
What we did
We created a cloud-based infrastructure for our data operations, leveraging Apache Airflow to run pipelines, and providing the analytics departments to get insights on the data. As part of our migration efforts, we transitioned to a robust Airflow deployment for data ingestion with integrated monitoring. In addition, we integrated and enriched external data sources.
The infrastructure deployment process was automated and cost-effective with state-of-the-art tooling, ensuring efficiency and resource optimization. Additionally, we maintained compliance with German Regulatory requirements for Health Care Apps throughout the development of our data pipelines.
Challenge
aidhere is on a mission to help people live healthier life. With the dynamic lifestyle now, it is important that products integrate seamlessly in the patient’s lifestyle. To be successful in this mission, aidhere wants to harvest the power of data and advanced analytics. To implement these data initiatives, they must navigate multiple challenges, including managing different data sources, securing sensitive health data, dealing with various data types, and balancing performance with cost efficiency. By effectively addressing these aspects, businesses can stay competitive and thrive in today's dynamic landscape.
Solution
Our team successfully implemented a cloud infrastructure that is both scalable and reproducible, specifically tailored for running Airflow ETL pipelines in the health care context.
We designed and built a robust process for efficiently fetching data from multiple sources. Additionally, we handled the migration of existing code to Airflow while seamlessly incorporating new requirements. As part of our efforts, we implemented analytics tooling to enhance data visibility and provided actionable alerts to promptly notify the team when data is ready for use.
Result
Our collaboration with aidhere brought about significant improvements in the visibility, reliability, and performance of their data processes. By implementing automated recovery and alerting mechanisms, we expedited issue resolution within the data pipelines. This not only enhanced operational efficiency but also enabled the exploration and development of new analytic use cases, backed by appropriate resources.
Furthermore, our establishment of an automated and cost-effective infrastructure deployment allowed aidhere to maintain separate development and production environments. This segregation instilled confidence in the development team's deployment processes while creating a conducive environment for experimentation and innovation.
Dr. Tobias Lorenz, Co-Founder & CTO
Data Max approach to build highly automated and cost-effective solutions, allowed us to efficiently optimize our operations. The team at Data Max is very flexible and competent in navigating various technology challenges, which greatly contributed to the success of the project.
I would confidently recommend Data Max to any organization in need of reliable support for their data infrastructure needs. Data Max was very flexible to accommodate our requirements.