技术
- 分析与建模 - 机器学习
- 平台即服务 (PaaS) - 应用开发平台
适用行业
- 消费品
- 运输
适用功能
- 物流运输
- 维护
用例
- 最后一英里交付
- 交通模拟
服务
- 数据科学服务
关于客户
Grip 是一家数据驱动型公司,为在美国各地运输易腐烂货物的电子商务企业提供智能运输解决方案。该公司每月通过其平台处理数十万份订单,为运输餐包、冷冻面包和面食、糕点的公司提供服务、宠物食品、鲜花和其他易腐烂的物品。 Grip 的平台集成了各种数据源,包括 Shopify、ShipStation、不同的仓库管理系统、天气数据 API、承运商定价和交货时间跟踪,以及 Zendesk 和 Dynamics 等客户支持系统。该公司利用这些数据提出最有效的运输建议,帮助客户降低损坏率和运输成本。
挑战
Grip 是一家为在美国各地运输易腐货物的电子商务企业提供服务的公司,每月通过其平台处理数十万份订单。该公司面临的挑战是处理和解释各种数据点,以提出最有效的运输建议。这些数据来自多个来源,包括 Shopify、ShipStation、不同的仓库管理系统、天气数据 API、承运商定价和交货时间跟踪以及 Zendesk 和 Dynamics 等客户支持系统。该公司需要整合这些数据来建议最佳的承运商、理想的制冷剂和绝缘材料、包装和材料以及其他运输物流。此外,交付完成后,Grip 需要发布分析结果,以便客户可以看到已发出的订单、它们去了哪里、该国出现瓶颈的地区以及该国表现良好的地区。
解决方案
Grip 采用 Databricks Lakehouse 平台来整合和处理其数据。该平台与天气提供商集成,因此预测是通过该平台进行处理的。它还跟踪客户反馈,包括之前运送到该国特定地区的记录。 Databricks 允许 Grip 构建端到端的机器学习模型和数据工程管道,为最终用户提供分析服务,并在一个平台内跟踪内部分析。 Grip 的管道完全通过 Databricks 工作流程进行编排,这使得在出现问题时可以轻松排除故障。警报集成与公司的团队联系在一起,因此他们可以在给客户带来问题之前重新运行或修复运行功能。 Grip 还使用 Databricks SQL Serverless 来驱动分析,这使其能够更定期地与客户共享数据。
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