Atlan > 实例探究 > 扩展 Postman 的数据团队:幕后见解和策略

扩展 Postman 的数据团队:幕后见解和策略

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技术
  • 分析与建模 - 大数据分析
  • 应用基础设施与中间件 - 数据库管理和存储
适用行业
  • 建筑物
  • 建筑与基础设施
适用功能
  • 销售与市场营销
用例
  • 施工管理
  • 时间敏感网络
服务
  • 数据科学服务
  • 系统集成
关于客户
Postman 是一个 API 协作平台,全球 50 万家公司的超过 1700 万人在使用。数据团队由25人组成,分为数据工程团队(8人)和数据科学团队(17人)。
挑战
Postman 的数据团队需要建立更好的入职、基础设施和流程,同时在一年内增长 4-5 倍。
解决方案
Postman 实施了集中式数据团队结构,为数据分析师创建了级别和层次结构,使用票务系统确定优先级,采用每周问题梳理会议进行项目分配,并实施了冲刺方法以实现持续输出和流程改进。
运营影响
  • The implementation of new processes and structures significantly improved the efficiency and effectiveness of Postman's data team. The move towards a more centralized team structure eliminated the issue of conflicting data systems and metrics. The introduction of a hierarchy provided clarity on roles and responsibilities within the team. The ticketing system on Jira and the weekly Issue Grooming sessions helped in managing work prioritization and project allocation, ensuring that tasks were distributed fairly and based on their impact and priority. The adoption of the sprint methodology encouraged the team to break down projects into smaller tasks, promoting continuous output and enabling the team to identify and address issues in a timely manner. These improvements have made the data team more comfortable with onboarding new hires, handling requests from the rest of the company, and planning their work.
数量效益
  • Postman's data team grew by 4-5x to 25 people in just over a year.
  • The company's valuation reached $5.6 billion, with its user base expanding to over 17 million people from 500,000 companies globally.
  • Nearly one quarter of the company is active on Looker every week, using the data processed by the Data Science Team.

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