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Real-Time Data Analytics and Machine Learning Accelerate Business Growth for TripActions
技术
- 分析与建模 - 机器学习
- 分析与建模 - 实时分析
适用行业
- 教育
- 设备与机械
用例
- 预测性维护
- 实时定位系统 (RTLS)
服务
- 数据科学服务
挑战
TripActions 的基础设施和数据存储解决方案无法满足分析数据容量和可扩展性需求，导致数据孤岛并增加总体拥有成本。历史数据从未被清理过，而分析数据以不同格式存储在各种数据库中，从而创建了多个数据孤岛，并使数据无法用于分析和机器学习。现有的数据解决方案在分析能力和可扩展性方面失败，增加了运营成本并抑制了业务增长。
关于客户
TripActions 是一家企业旅行管理组织，帮助控制商务旅行成本并通过轻松获得的商务旅行机会激励员工。
解决方案
Provectus 通过使用 AWS 产品迁移和合并历史数据，为实时流数据管道提供了统一的解决方案。他们在 Apache Kafka 之上构建了一个实时流解决方案，用于数据摄取、处理、丰富和转换。数据流设计为自动存储在 Amazon S3 和 AWS Glue 之上的数据湖中，并针对 Amazon Athena 的亚秒级查询进行了优化。现有平台的历史数据已迁移到单独的数据湖，以确保分析和机器学习的数据一致性和可用性。
运营影响
数量效益
相关案例.
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The application arises from the need to monitor and anticipate the problems of one or more machines managed by a PLC. These problems, often resulting from the accumulation over time of small discrepancies, require, when they occur, ex post technical operations maintenance.
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