利用 AWS 增强数据处理：GumGum 案例研究
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适用行业
- 石油和天然气
适用功能
- 销售与市场营销
用例
- 库存管理
关于客户
GumGum 是一家以创造图像广告类别而闻名的知名公司。该公司提供基于其专利图像识别技术的产品，提供程序化、本机和社交分析软件解决方案。 GumGum 吸引了 4 亿访问者，他们查看了 2,000 多家优质出版商的图像和内容。与传统展示选项相比，该公司客户的广告可见度提高了 20%，参与度提高了 10 倍。这将为营销人员带来卓越的品牌提升，并为出版商增加收入。 GumGum 与 AdAge 美国 100 强广告支出公司中超过一半的公司合作，其中包括迪士尼、欧莱雅、丰田和三星。该公司总部位于加利福尼亚州圣莫尼卡，在美国和英国设有六个办事处。
挑战
GumGum 是一家领先的程序化、原生和社交分析软件解决方案提供商，在管理数据方面面临着重大挑战。该公司每天生成超过 10 亿个事件，相当于约 6 TB 的数据。需要持续处理如此大量的数据，以消除瓶颈并加快客户的决策速度。该公司迫切需要一种能够快速扩展的解决方案，以处理快速增长的流量和数据。挑战不仅在于管理数据量，还在于实时处理数据以便为客户提供有价值的见解。
解决方案
GumGum 求助于 Amazon Web Services (AWS) 来解决其数据管理挑战。该公司现在运行生成事件数据的广告服务器，这些数据每小时写入日志并上传到 Amazon Simple Storage Solution (Amazon S3)。然后输出存储在 Amazon Redshift 中。为了管理生产、测试和开发的工作流程，GumGum 使用 Amazon Data Pipeline 服务。对于库存预测和每小时数据处理，该公司使用 Amazon Elastic MapReduce (Amazon EMR) 分别运行 Apache Spark 和 Hadoop。此外，GumGum 为其用户提供专有的仪表板，显示来自报告服务器的数据，确保客户能够获得实时见解。
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