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Kyligence:金融服务数据驱动洞察的最佳实践白皮书(英文版)(29页).pdf

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1、Alice LaPlanteBest Practices for Getting Actionable Insight from Data Early and OftenSpeeding from Data to Insight in Financial ServicesCompliments ofAlice LaPlanteSpeeding from Data to Insight inFinancial ServicesBest Practices for Getting Actionable Insightfrom Data Early and OftenBostonFarnhamSeb

2、astopolTokyoBeijingBostonFarnhamSebastopolTokyoBeijing978-1-492-03310-3LSISpeeding from Data to Insight in Financial Servicesby Alice LaPlanteCopyright 2018 OReilly Media.All rights reserved.Printed in the United States of America.Published by OReilly Media,Inc.,1005 Gravenstein Highway North,Sebast

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本文主要讨论了金融服务业在数据洪流中面临的挑战和解决方案。主要观点如下: 1. 金融服务业正在经历数据洪流,这对企业既是机遇也是挑战。数据是当今企业最主要的竞争优势,但同时数据量巨大且难以获取。 2. 金融服务业在数据湖上面临的问题包括:需要大量专业技能来利用数据湖中的数据,现有工具难以满足性能需求,以及数据湖本身难以提供即时的洞察。 3. Apache Kylin是解决这些问题的一个开源解决方案。它利用Hadoop的扩展能力和MapReduce的分布式处理能力,以极快的速度处理SQL查询,同时保留了传统OLAP模型的特点,使得业务分析师能够轻松适应。 4. 商业大数据解决方案和开源大数据解决方案各有利弊。商业解决方案稳定可靠,但成本高,且存在锁定效应;开源解决方案免费,透明度高,但需要依赖社区支持。 5. 金融服务业正在使用数据进行客户和市场趋势监测、个性化消息传递、定制客户服务、移动应用开发、欺诈检测、人工智能决策以及通过新产品和服务来货币化数据。
数据湖在金融服务中面临哪些挑战? Apache Kylin如何解决数据湖的洞察力差距? 金融服务公司应如何选择大数据解决方案?
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