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Revamping Data Management for Enhanced Patient Care: A Case Study on Integra Life Sciences
技术
- 分析与建模 - 机器学习
- 功能应用 - 仓库管理系统 (WMS)
适用行业
- 建筑物
- 生命科学
适用功能
- 物流运输
- 仓库和库存管理
用例
- 拣选/分拣/定位
- 时间敏感网络
服务
- 数据科学服务
- 测试与认证
挑战
当 COVID-19 大流行扰乱医疗供应链时，全球医疗技术提供商 Integra Life Sciences 面临着重大挑战。该公司需要全面了解全球供需情况，以确保其产品可用于择期手术。然而，其老化的数据仓库限制了其供应链的敏捷性，导致访问使用模式、库存水平和质量问题等关键数据的延迟。遗留仓库系统 IBM DataStage 既耗时又不灵活，阻碍了公司快速响应不断变化的需求的能力。该公司需要一个能够及时洞察库存和需求的解决方案，使其能够更有效地交付产品。
关于客户
Integra Life Sciences 是外科手术医疗技术的全球提供商。该公司的使命是通过确保其产品在正确的时间出现在正确的地点来提高选择性手术的可用性。这一过程在很大程度上依赖于数据，这有助于 Integra 的决策者确定需求在哪里形成、产品位于哪里以及如何最好地满足不断变化的需求。该公司在 COVID-19 大流行期间面临重大挑战，这扰乱了医疗供应链，并加剧了对全面、敏捷的数据管理系统的需求。
解决方案
Integra Life Sciences 开始了战略转型，以重新了解其库存并在充满挑战的时期推动增长。该公司聘请 Wipro 作为战略合作伙伴，并将其数据从旧数据仓库迁移到 Azure Databricks。 Integra 在其业务范围内构建了小型概念验证，重点关注构建下一代数据管道、实施 DevOps 以及创建可重用组件。公司迁移了500个数据对象，构建了700个数据管道。 Databricks Lakehouse 现在为企业数据仓库、人工智能、机器学习和物联网提供统一平台。在与旧系统并行运行三个月后，Integra 在九个月内就在其新的 Databricks Lakehouse 平台上上线。
运营影响
数量效益
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