Fivetran > Case Studies > Vida Health's Transformation: Personalized Healthcare through Modern Data Stack

Vida Health's Transformation: Personalized Healthcare through Modern Data Stack

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Technology Category
  • Analytics & Modeling - Big Data Analytics
  • Functional Applications - Enterprise Resource Planning Systems (ERP)
Applicable Industries
  • Healthcare & Hospitals
  • Oil & Gas
Applicable Functions
  • Product Research & Development
  • Quality Assurance
Use Cases
  • Experimentation Automation
  • Leasing Finance Automation
Services
  • Cloud Planning, Design & Implementation Services
  • Testing & Certification
About The Customer
Vida Health is a San Francisco-based digital health company founded in 2014. The company provides personalized virtual care to individuals with chronic conditions such as diabetes, obesity, and depression through employer-sponsored plans. To tailor support and resources to individual needs, Vida Health collects data on the customer's medical history, past insurance claims, lab test results, and log data from health-tech devices such as fitness trackers and digital scales. The data enables Vida Health to monitor user progress, adjust treatment plans as needed, and give users visibility into results via the Vida Health mobile app. The company has a team size of 400 and uses a data stack comprising dbt Cloud, Fivetran Enterprise, Google Cloud, BigQuery, and Looker.
The Challenge
Vida Health, a digital health company, was facing challenges with its data infrastructure. The company collects data on customers' medical history, past insurance claims, lab test results, and log data from health-tech devices to provide personalized virtual care. However, their custom-built solution using Python scripts and cron jobs to load and transform data in BigQuery was not scalable and often failed when data volume spiked. The pipeline was poorly documented and understood by only a few people on the data team, leading to reporting downtime of 2-3 days when issues arose. The company had recently consolidated its data engineering, data science, and data analytics functions into one team, aiming to improve collaboration. However, the existing data infrastructure was not reliable or accessible enough to best serve their customers and meet their goal of onboarding more than ten new clients in less than six months.
The Solution
Vida Health implemented Fivetran and dbt Cloud to transform their data infrastructure. Fivetran was used to centralize data from all their SaaS applications and proprietary Protected Health Information (PHI) from multiple sources into one source-of-truth warehouse. This provided built-in automation and security, especially crucial when handling health data. The company now uses Fivetran to centralize data from 148 different connectors into one BigQuery. Once the data was loaded into BigQuery with Fivetran, the team used dbt Cloud to refactor old pipeline code into modular SQL queries that could be more easily read, reused, and maintained. dbt Cloud made the data transformation process accessible to Vida Health employees across clinical research, product, and data teams, enabling them to share knowledge, add more precision to their data insights and product, and move faster. The company now uses built-in features from dbt Cloud and Fivetran to prevent issues that could create pipeline downtime and ensure a quick recovery when incidents occur.
Operational Impact
  • The implementation of Fivetran and dbt Cloud has resulted in a more resilient and maintainable pipeline for Vida Health. The company can now easily pinpoint issues with data ingestion as they come up, thanks to having access to pipeline creation and monitoring all in one place with Fivetran. The fully managed connectors with schema migration and automation built in ensure data is always available. The team uses dbt Cloud's data lineage to trace bugs, snapshots to detect data changes over time, and built-in CI support to standardize testing and improve data quality. This has increased their velocity as they spend less time on maintenance. The modern data stack has provided Vida Health with the foundation needed to provide best-in-class care to their clients, driven by data.
Quantitative Benefit
  • 148 active connectors ingest data from various databases and SaaS data sources
  • Reduced time to generate a KPI for executives from 3 months to 1 day
  • 80% of work to create new data products can now be self-served by the analytics team, up from 20%

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