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US Foods Analyzes Transactions from 300,000 Customers with Snowflake and DataRobot
技术
- 基础设施即服务 (IaaS) - 云计算
- 分析与建模 - 预测分析
适用行业
- 食品与饮料
适用功能
- 销售与市场营销
- 商业运营
用例
- 预测性维护
- 供应链可见性(SCV)
服务
- 数据科学服务
- 云规划/设计/实施服务
挑战
美国食品公司是美国最大的食品公司之一，其传统的本地数据仓库面临巨大挑战。该系统需要不断维护，经常发生资源争用，并且无法以经济实惠的方式存储超过两年的数据。由于系统的用户界面违反直觉、无法加载大型数据集以及 BI 功能有限，业务分析师需要数周时间才能准备一份报告。报告延迟导致一些业务用户从孤立的 Microsoft Access 数据库和 Excel 电子表格中寻求见解。通过数据科学建模来预测客户忠诚度和流失率根本是不可能的。美国食品公司评估了几种云数据管理解决方案，但没有一种能够提供性能和经济实惠的完美组合。
关于客户
US Foods 是一家食品服务分销商，也是美国最大的食品公司之一。该公司总部位于伊利诺伊州罗斯蒙特，拥有约 26,000 名员工。US Foods 为约 300,000 家餐厅和食品服务运营商提供广泛的食品产品、烹饪设备、用品和技术目录。该公司使用数据分析和数据科学来监控绩效、预测流失率并加速增长。
解决方案
US Foods 采用了 Snowflake 的云数据平台，该平台经过扩展，成为其交易数据的单一分析存储库。Snowflake 的 Python 连接器和 Amazon S3 的批量加载功能使每天能够提取大量数据集而不会造成瓶颈。Snowflake 对 SQL 的原生支持以及简洁、易于导航的界面加速了报告创建。DataRobot 集成实现了客户流失率的预测分析，可识别出需要 US Foods 保留团队主动联系的高风险客户。该解决方案为 US Foods 的数据管理和预测分析能力提供了显著的改进。
运营影响
数量效益
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