技术
- 分析与建模 - 机器学习
- 分析与建模 - 预测分析
适用行业
- 消费品
- 零售
适用功能
- 物流运输
- 采购
用例
- 库存管理
- 供应链可见性(SCV)
服务
- 云规划/设计/实施服务
- 数据科学服务
关于客户
强生公司是全球消费品和药品的基石供应商,150 多年来一直为世界各地的企业、患者、医生和人们提供服务。该公司提供广泛的产品,从维持生命的医疗设备到疫苗、非处方药和处方药,以及用于制造这些产品的工具和资源。强生公司的业务战略的核心是确保产品按时交付到正确的地点,并以公平的价格出售,以便消费者能够有效地获取和使用他们的产品。
挑战
强生公司是一家全球消费品和药品供应商,在管理其供应链数据方面面临着重大挑战。该公司通过收购实现增长,形成了一个分散的数据系统,具有不同的优先级和独特的配置。数据主要是手动提取和分析的,限制了速度和可扩展性的机会。断开连接对客户服务产生了负面影响,并阻碍了战略决策。该公司还面临着在全球范围内优化库存管理和成本的挑战,这需要准确且丰富的数据。无法理解和控制支出和定价可能会导致对未来战略决策和举措的识别有限,从而可能错失实现 6MM 上涨空间的机会。
解决方案
强生公司踏上了在整个组织内实现数据民主化的旅程。该公司从 Hadoop 迁移到 Azure 云上使用 Databricks Lakehouse Platform 的统一方法。目标是创建一个通用数据层,以提高性能,提供更多功能,改进决策,为工程和供应链运营带来可扩展性,并轻松实时有效地修改查询和见解。该公司用单一数据视图取代了 35 多个全球数据源,数据科学家、工程师、分析师和应用程序可以轻松使用这些数据。新的数据基础设施可以处理大约 15 分钟的 SLA,以实现数据交付和可访问性。 Lakehouse 的数据管理方法提供了一个通用数据层来提供大量可以根据业务需求进行扩展的数据管道。
运营影响
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