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AccuWeather's Transformation: Predicting Business Impact of Weather with Azure Machine Learning
技术
- 分析与建模 - 机器学习
- 应用基础设施与中间件 - 数据库管理和存储
适用行业
- 教育
- 设备与机械
适用功能
- 物流运输
- 销售与市场营销
用例
- 库存管理
- 预测性维护
服务
- 云规划/设计/实施服务
- 数据科学服务
挑战
AccuWeather 是全球领先的天气预报提供商，面临着为企业客户提供定制天气影响预测的挑战。企业需要的不仅仅是天气数据；他们想要预测天气将如何影响他们的运营。最初，AccuWeather 在临时协商的基础上提供这项服务，这是一项劳动密集型工作。客户将分享他们的销售历史数据，AccuWeather 将让数据科学家清理数据并创建自定义模型。然而，这个过程不可扩展。 AccuWeather 希望实现这项服务的自动化，允许客户在线上传数据并生成自动预测。然而，他们担心当时拥有的分析工具不允许他们提供高质量的预测。
关于客户
AccuWeather, Inc. 总部位于宾夕法尼亚州州立学院市，是全球领先的天气预报提供商。它为全球 230 万个地点提供未来 90 天内每小时和未来两小时内每分钟的 100 多个参数（包括温度、湿度、雨、雪和冰）的每分钟预报。 AccuWeather 从陆地、船舶、飞机、卫星和雷达收集数十万个实时天气观测数据，并使用其获得专利的 AccuWeather 预报引擎处理这些数据。超过 180,000 个网站、200 个电视台、900 个广播电台和 600 份报纸提供 AccuWeather 天气预报。全球总共有近 20 亿人依靠 AccuWeather 来帮助他们规划生活、保护他们的业务并保持安全。
解决方案
AccuWeather 求助于 Microsoft Azure 为企业客户构建自动化、可扩展的天气预报服务。他们选择 Azure 是因为其可靠的基础设施即服务产品，以及丰富且快速发展的平台即服务组合，包括大数据、机器学习和人工智能功能。 AccuWeather 首先将其 API 业务迁移到 Azure，后者提供了一种更具可扩展性、更具成本效益的服务管理方式。然后，他们使用 Azure Blob 存储、Azure 数据工厂和 Azure SQL 数据库等服务转移了大数据存储和处理。为了创建高度准确的预测，他们使用了 Azure 的机器学习工具，该工具功能强大，但可以使用 R 和 Python 代码进行自定义。 2017 年 5 月，AccuWeather 推出了 AccuWeather D3 Express，这是一款基于云的分析产品，可量化破坏性天气对业务的影响。然后他们开发了 D3 Advanced，它使用机器学习提供更多定制的预测。
运营影响
数量效益
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