通过数据集中实现终身价值优化：BlaBlaCar 案例研究
技术
- 分析与建模 - 大数据分析
- 基础设施即服务 (IaaS) - 云数据库
适用行业
- 水泥
- 运输
适用功能
- 物流运输
- 销售与市场营销
用例
- 需求计划与预测
- 最后一英里交付
服务
- 数据科学服务
关于客户
BlaBlaCar 是一家开创性公司，推出了全球首个在线拼车预订服务。这种创新方法将拼车变成了一种可行的交通方式。该公司经历了快速发展，拥有超过 1000 万会员，业务遍及 13 个国家。它继续以每年200%的速度扩张。 BlaBlaCar 从事在线汽车共享平台行业，主要在欧洲和印度市场。该公司数据科学的主要用例是生命周期价值优化（CRM）。
挑战
BlaBlaCar 是世界上第一个在线拼车预订服务，在访问和利用其数据方面面临着重大挑战。该公司的商业智能 (BI) 团队严重依赖 IT 团队进行报告和分析。数据检索过程非常耗时且重复，通常需要数天才能交付所请求的数据。公司数据源异构、分散，BI团队难以按需获取数据。我们面临的挑战是找到一种能够清理、整合和集中这些数据源的解决方案，以便全球 BI 团队轻松、立即访问。
解决方案
BlaBlaCar 采用 Data Science Studio 来自动清理和集中数据，以实现全球按需访问。开发人员和 BI 数据经理构建了一个流，可以自动从各种来源检索数据，包括 SQL 数据库、社交网络数据、用户评论和合作伙伴日志。然后，数据被聚合并存储在 Vertica 数据库中，并针对大数据环境中的分析计算和复杂查询进行了优化。该解决方案允许业务、营销和 BI 团队构建和查看报告，而无需在 SQL 数据库上重新生成复杂且昂贵的查询。 BI 团队使用连接到 Vertica 数据库的 Tableau Software 来创建数据可视化。
运营影响
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