F500 Wholesaler in U.S. Depends on Sigma to Meet SLAs
公司规模
1,000+
地区
- America
国家
- United States
产品
- Sigma
- Snowflake
- Tableau
技术栈
- Cloud Data Warehouses
- Spreadsheet Interface
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Customer Satisfaction
- Productivity Improvements
技术
- 分析与建模 - 预测分析
- 分析与建模 - 实时分析
- 平台即服务 (PaaS) - 数据管理平台
适用行业
- 食品与饮料
适用功能
- 商业运营
- 物流运输
用例
- 预测性维护
- 过程控制与优化
- 供应链可见性(SCV)
服务
- 数据科学服务
- 系统集成
关于客户
The customer is a leading foodservice distributor in the United States, partnering with 300,000 restaurants and foodservice operators to help their businesses succeed. The company has a large dataset, including multi-billion rows of service level data, which is accessed by more than 2000 employees multiple times a day through the Service Level Impact dashboard in Tableau. The company aims to ensure fulfillments are achieved and SLAs are met, but faced challenges due to scale limitations and the need for timely data access.
挑战
The foodservice distributor faced significant challenges in managing its vast dataset, which included multi-billion rows of service level data. Employees needed timely access to this data to conduct root cause analysis and resolve issues to meet SLAs. However, scale limitations and the inability to anticipate ever-changing data requirements hindered their ability to access all necessary data. The BI team spent 20% of its time answering ad hoc questions and extracting data, which needed continuous refreshing as issues evolved. This lack of timely data access negatively impacted employees' ability to understand and resolve issues, leading to missed SLAs, penalties, and customer retention and acquisition challenges.
解决方案
The foodservice distributor implemented Sigma, a cloud-native solution purpose-built for Snowflake and cloud data warehouses. This allowed employees direct access to live data in Snowflake, ensuring everyone worked with the same current data without stale extracts or conflicting insights. Sigma provided unlimited scale and speed, enabling employees to analyze and filter billions of rows of transactional data without rendering or latency delays. The spreadsheet interface of Sigma made iterative ad hoc analytics accessible to anyone, especially those accustomed to analyzing data in spreadsheets. Employees could now analyze data and create pivot tables in Sigma, quickly addressing potential issues before they became serious problems.
运营影响
数量效益
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