技术
- 分析与建模 - 机器学习
- 平台即服务 (PaaS) - 应用开发平台
适用行业
- 建筑与基础设施
- 零售
适用功能
- 维护
- 销售与市场营销
用例
- 预测性维护
- 时间敏感网络
服务
- 云规划/设计/实施服务
- 数据科学服务
关于客户
Paul Hewitt 是著名的珠宝和配饰品牌,目前正处于在线之旅的早期阶段。该公司曾使用 Supermetrics 来分析广告支出,但很快就超出了其能力范围。分析团队手动将 Supermetrics 的数据输入到电子表格中,以确定哪些渠道提供了最佳回报。为了满足日益复杂的供应链的需求,该公司投资了 ERP 系统 Microsoft Dynamics NAV,并开始使用 Microsoft Power BI 提供数据进行分析。该公司的目标是通过将整个业务的数据集成到云数据平台上的一个位置来转型为数据驱动型企业。
挑战
Paul Hewitt 是一个珠宝和配饰品牌,由于其现有工具 Supermetrics 的局限性,在管理和分析其广告支出方面面临着挑战。由三名员工组成的分析团队必须手动将数据输入电子表格,以确定最有效的营销渠道,这个过程既耗时又容易出错。为了满足日益复杂的供应链的需求,该公司投资了 ERP 系统 Microsoft Dynamics NAV,并开始使用 Microsoft Power BI 提供数据进行分析。然而,该公司希望通过将整个业务的数据集成到云数据平台上的一个位置,将其数据战略提升到一个新的水平,目标是转型为数据驱动的业务。
解决方案
Paul Hewitt 决定使用第一方 Microsoft 提供商 Databricks 作为其数据分析平台。这是一个自然的选择,因为该公司已经拥有 Microsoft Azure 云平台。 Databricks 帮助消除了数据孤岛,实现了整体分析和数据科学,并为未来的机器学习用例奠定了基础。该公司还使用 Databricks 的 Azure 和 Delta Lake 作为数据湖,并使用 Power BI 进行可视化。为了实现数据源管道的自动化,该公司选择了 ELT 提供商 Fivetran,因为它的功能强大且易于使用。 Fivetran 的设置是自动将来自多个广告渠道 API 的数据加载到数据湖中,从而更好地洞察营销支出。
运营影响
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