Technology Category
- Application Infrastructure & Middleware - Data Exchange & Integration
- Application Infrastructure & Middleware - Middleware, SDKs & Libraries
Applicable Industries
- Equipment & Machinery
Applicable Functions
- Quality Assurance
Use Cases
- Experimentation Automation
- Regulatory Compliance Monitoring
Services
- Cloud Planning, Design & Implementation Services
- Testing & Certification
About The Customer
Testing for All is a non-profit organisation based in the UK, launched to provide mass Covid-19 testing. The organisation devised a low-cost, high-volume service for individuals and businesses, aiming to deliver 5,000 high-quality Covid-19 tests a day at half the price of other services. The process involved a six-step procedure, starting with registration and dispatching a test kit, and ending with receiving lab results. The Royal Mail postal service was a key partner throughout the process. The organisation needed a solution that could handle personal data, medical test results, and biological samples while maintaining a prompt and user-friendly service at scale.
The Challenge
Testing for All, a UK-based non-profit organisation, was launched to provide mass Covid-19 testing at a low cost. The organisation aimed to deliver 5,000 high-quality Covid-19 tests a day at half the price of other services. However, they faced a significant challenge in managing personal data, medical test results, and biological samples while maintaining a prompt and user-friendly service at scale. The process involved a six-step procedure, starting with registration and dispatching a test kit, and ending with receiving lab results. The organisation needed a privacy-centric technology stack that could handle the complexity of the process and ensure speed and efficiency in both the eCommerce part (signing up and ordering the kits) and the science part (the labs providing a range of swabbing techniques).
The Solution
To address the challenge, Testing for All implemented Fivetran, an automated data integration tool. Fivetran was chosen for its intuitive use, automation, full management, compatibility with all data sources, and compliance with data regulations. It played a crucial role as a scheduler, automating the movement of data from connected sources to Google BigQuery at pre-set intervals. After the initial sync, Fivetran incrementally pulled updates of new or changed data from the source, ensuring that only new data was uploaded and avoiding duplication. The data warehouse chosen was Google BigQuery, with Data Studio as their data visualisation tool. Data from eCommerce, fulfilment, and laboratory partners was all joined up and made available to query and collate in reports. Compatibility with Python and Pandas for pre-processing certain data fields was also crucial for regulatory compliance.
Operational Impact
Quantitative Benefit
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