技术
- 分析与建模 - 预测分析
- 分析与建模 - 实时分析
适用行业
- 电子商务
- 运输
适用功能
- 设施管理
- 物流运输
用例
- 最后一英里交付
- 实时定位系统 (RTLS)
服务
- 硬件设计与工程服务
- 系统集成
关于客户
Pitney Bowes 是一家全球科技公司,致力于简化电子商务、运输和邮寄的复杂性。该公司每年通过 16 个配送设施管理 4 亿个邮件包裹,为全球 750,000 家企业提供服务。 Pitney Bowes 拥有超过 11,000 名员工,是电子商务、运输和邮寄行业的主要参与者。该公司的服务对于全球企业至关重要,其有效且高效地管理和跟踪包裹的能力是其成功的关键。该公司最近的数据堆栈现代化使其能够跟踪每个包裹并预测邮件量的变化,从而预测每个设施的劳动力需求。
挑战
Pitney Bowes 是一家简化电子商务、运输和邮寄的全球科技公司,其数据管理面临着重大挑战。该公司缺乏关键业务决策所需的高质量实时数据。其企业信息管理 (EIM) 团队正在努力解决孤立的数据、缺乏可扩展性和低效的技术支出等问题。员工将数据粘贴到 Excel 电子表格中以进行执行报告和分析,这往往会加剧问题。该公司还遇到了下游问题,例如影响服务水平协议 (SLA) 目标的延迟到达的软件包。他们缺乏检测延误并及时通知客户的能力,从而导致声誉风险。当在线购物增加十倍时,新冠疫情加剧了这些数据挑战,导致包裹数量增加十倍。该公司的旧数据基础设施无法处理每天 8 亿个包裹的基于事件和电子邮件的数据操作。捕获的数据至关重要,但将其聚合并整合到中央分析仓库需要数天时间,当到达领导团队时,这些数据就已经过时了。
解决方案
Pitney Bowes 决定通过实施 Fivetran 和 Snowflake 对其数据堆栈进行现代化改造。 Fivetran 取代了 Pitney Bowes 的所有自定义批处理脚本和提取、转换、加载 (ETL) 流程。该团队使用 Fivetran 的开箱即用连接器为 SAP、Salesforce、Facebook、Kafka 和 Kinesis 等多个关键业务应用程序快速构建管道。 Fivetran 能够将一批负载从 31 小时减少到不到两小时,另一批负载从几天减少到不到一小时。这种新的数据流有效地收集和汇总了来自 16 个设施的 700,000 个物联网设备的数据。 Fivetran 基于日志的变更数据捕获 (CDC) 连接器捕获所有数据更改,并消除了处理加载时间和对源系统的影响。 Fivetran 本地数据处理帮助 Pitney Bowes 移动大量数据并消除其基础设施瓶颈。该团队还利用 Fivetran 本地数据处理来同步 SAP 数据,这在以前是一个挑战。 Fivetran 的 SAP 连接器在七小时内将大量数据完全同步到 Snowflake,性能显着提高。
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