Fivetran > 实例探究 > Fivetran 在加速非营利组织 Covid-19 测试方面的作用

Fivetran 在加速非营利组织 Covid-19 测试方面的作用

技术

应用基础设施与中间件 - 数据交换与集成
应用基础设施与中间件 - 中间件、SDK 和库

适用行业

设备与机械

适用功能

质量保证

用例

实验自动化
监管合规监控

服务

云规划/设计/实施服务
测试与认证

关于客户

Testing for All 是一家总部位于英国的非营利组织，旨在提供大规模 Covid-19 检测。该组织为个人和企业设计了一种低成本、大容量的服务，旨在每天以其他服务一半的价格提供 5,000 次高质量的 Covid-19 测试。该过程涉及六个步骤，从注册和发送测试套件开始，到接收实验室结果结束。英国皇家邮政 (Royal Mail) 邮政服务是整个过程中的关键合作伙伴。该组织需要一种能够处理个人数据、医学检测结果和生物样本的解决方案，同时保持大规模的及时且用户友好的服务。

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挑战

总部位于英国的非营利组织“Testing for All”成立，旨在以低成本提供大规模 Covid-19 检测。该组织的目标是每天以其他服务一半的价格提供 5,000 次高质量的 Covid-19 测试。然而，他们在管理个人数据、医学测试结果和生物样本，同时保持大规模的及时和用户友好的服务方面面临着重大挑战。该过程涉及六个步骤，从注册和发送测试套件开始，到接收实验室结果结束。该组织需要一个以隐私为中心的技术堆栈，可以处理流程的复杂性，并确保电子商务部分（注册和订购套件）和科学部分（提供一系列拭子技术的实验室）的速度和效率。

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解决方案

为了应对这一挑战，Testing for All 实施了 Fivetran，这是一种自动化数据集成工具。 Fivetran 因其直观使用、自动化、全面管理、与所有数据源兼容以及符合数据法规而被选中。它作为调度程序发挥着至关重要的作用，可以按照预设的时间间隔自动将数据从连接的源移动到 Google BigQuery。初始同步后，Fivetran 逐渐从源中提取新数据或更改数据的更新，确保仅上传新数据并避免重复。选择的数据仓库是 Google BigQuery，并以 Data Studio 作为其数据可视化工具。来自电子商务、履行和实验室合作伙伴的数据全部合并在一起，并可在报告中查询和整理。与 Python 和 Pandas 预处理某些数据字段的兼容性对于法规遵从性也至关重要。

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运营影响

The implementation of Fivetran resulted in ongoing process optimisation for Testing for All. The combination of 'out-of-box' connectors to all the non-profit's data sources and automated integration with Google BigQuery was pivotal in delivering a high-quality service in a tight timeframe. The whole testing journey could be visualised, and reasons for incompletion analysed. Potential points of failure, like different turnaround times in the laboratories, could be optimised by aligning customer needs to the most appropriate facility. Faster labs are more expensive, for example, and best used when someone has a flight to catch. Personal information, like date-of-birth, is stored as age brackets, 40-59 for example, which protects personal privacy while still providing valuable data for analysis.

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数量效益

Highly detailed visibility into the performance of the end-to-end testing process
Speed and quality of service maintained
Automation and integration saves time for a small team

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