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Fivetran's Role in Accelerating Covid-19 Testing for Non-Profit Organisation
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
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。
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。
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。
运营影响
数量效益
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