乳制品巨头 Arla Foods 将数据集中在 Azure 中以提高生产力和灵活性
技术
- 应用基础设施与中间件 - 数据可视化
- 基础设施即服务 (IaaS) - 云计算
适用行业
- 消费品
- 电网
适用功能
- 维护
- 产品研发
用例
- 减废预测
- 时间敏感网络
服务
- 系统集成
- 培训
关于客户
Arla Foods 是一家总部位于丹麦的乳制品公司，也是世界第五大乳制品公司。该公司拥有丰富的历史，可以追溯到 1800 年代，当时第一家合作乳品厂在瑞典成立。 Arla 是农民所有，所有收入都返还给农场主。该公司非常重视其奶制品从奶牛到消费者的整个过程，记录和追踪每一步。 Arla 致力于动物福利、产品质量和安全的高标准，结合传统工艺和技术，确保产品尽可能贴近自然。该公司拥有 10,000 多名员工，从事消费品行业。
挑战
Arla Foods 是全球第五大乳制品公司，其数据管理面临着重大挑战。该公司拥有复杂的、意大利面条般的数据系统结构，每个系统都面临着独特的维护和管理挑战。维护这些系统的成本不断增加，员工花在管理系统上的时间比从系统内的数据中获取见解的时间还要多。该公司拥有数千个不同的应用程序，但没有一个是可转移的，从而形成了一组效率极低的孤立解决方案。此外，该公司使用 Microsoft Power BI 作为可视化工具，但如果没有适当的数据架构，该工具很快就会过载并开始失败。该公司认识到其当前流程不起作用，并着手寻找既能节省资金又能推动业务发展的解决方案。
解决方案
Arla Foods 决定使用 Azure 集中其数据。该公司使用 SAP BW on HANA 进行财务数据和分析，并将所有非 SAP 数据移至云端。 Azure 提供了完整解决方案所需的所有工具，无需任何第三方工具。该公司在 Azure 上开发了一个数据基础，为公司任何地方的数据创建了一个集中位置以供摄取和使用。然后，集中的数据可用于满足各种业务需求，从 Power BI 中的自助报告到探索性分析以及为数据驱动的应用程序提供支持。该公司还使用 Azure 数据工厂从其他本地源提取数据并将其原始存储在 Azure Data Lake Store Gen2 中。然后，数据被清理并转换为精选数据层，也存储在 Azure Data Lake Store Gen2 中。为了进行报告，整理的数据层被加载到每个用例构建的特定数据集市中。新的架构允许 Power BI 得到充分利用，可以管理容量，并且可以显着简化数据模型以避免性能问题。
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