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SpotOn Accelerates Reporting with Fivetran Transformations for dbt Core
技术
- 基础设施即服务 (IaaS) - 云数据库
- 平台即服务 (PaaS) - 应用开发平台
适用行业
- 电网
- 设备与机械
适用功能
- 产品研发
用例
- 租赁金融自动化
- 时间敏感网络
服务
- 云规划/设计/实施服务
挑战
SpotOn 是一家快速发展的软件和支付公司，在有效地将捕获的客户交易数据转化为为客户提供快速、可靠且信息丰富的报告方面面临着重大挑战。随着公司规模的扩大，将数据转化为客户和内部利益相关者报告的复杂性不断增加，客户数据分散在 30 个未连接的 MySQL 数据库中。工程团队缺乏用于高效生成报告的中央存储库。 Snowflake 中使用存储过程的现有数据转换过程变得越来越复杂且资源密集，单个表背后有超过 2,000 行代码。如果没有版本控制，则不会自动监视或记录更改，这使得质量保证非常耗时，并且需要为每个新用例从头开始编写代码。这导致了高成本、资源密集型流程和次优结果，影响了公司快速扩展以满足不断增长的客户需求的能力。
关于客户
SpotOn 是发展最快的软件和支付公司之一，为各种类型和规模的企业提供全面的、基于云的技术。收购 Appetize 后，SpotOn 的客户群不断扩大，包括麦迪逊广场花园、芬威球场和大都会人寿体育场等企业场馆，这些场馆都有独特的需求和复杂的数据。该公司的产品团队的任务是高效地将捕获的客户交易数据转化为为客户提供快速、可靠、信息丰富的报告，而其内部数据团队则利用数据来优化内部运营。
解决方案
为了应对这些挑战，SpotOn 转向 Fivetran、Snowflake 和 dbt。 Fivetran 用于将客户的所有客户数据从 30 个不同的 MySQL 数据库无缝移动到 Snowflake，提供安全的数据基础，然后可以大规模转换以满足他们的各种分析需求。借助 Fivetran Transformations for dbt Core，SpotOn 能够为客户提供更快、更可靠的自动化报告，同时节省时间和成本。 dbt Core 模块化了 2,000 行转换代码，使数据模型更具可读性、更易于调试，并可通过 jinja 模板进行扩展。通过将 dbt 项目集成到 Fivetran 中，面向 dbt Core 的 Fivetran Transformations 可以编排这些模型在 Fivetran 连接器加载后自动运行，从而无需自定义脚本、第三方工具或 DevOps。 SpotOn 的数据工程团队还使用 dbt Cloud 将多个数据库中的大量数据转化为强大的内部分析和 BI，从而实现协作、数据驱动的增长。
运营影响
数量效益
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