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引用次数: 3
摘要
如今,组织不仅需要管理大量数据,还需要从现有数据中生成见解。这些见解有助于他们更好地了解客户并预测市场趋势。有了这个计划,他们可以利用云平台来实现这一目标,因为它管理着更高的数据量、速度和变化。这个云平台使他们能够提供弹性和高效的计算和存储资源。它们还提供了许多现成的工具,用于在不同阶段构建数据分析。此外,按需定价模型允许组织为他们所消费的东西付费。它将组织消费模式从资本支出转变为经营支出。它极大地减少了构建数据分析解决方案和实施其他创新想法的初始资本投资。本文强调了鼓励组织在云中构建数据分析的主要原因。它还展示了如何为云中的电子商务平台构建数据分析框架,以及如何将机器学习模型集成到数据分析流程中,以创建更复杂的分析。AWS是Amazon Web Services首屈一指的公共云平台,通过真实的商业案例来演示这些概念和实践。
Data Analytics Architectures for E-Commerce Platforms in Cloud
Today, organizations not only need to manage larger volumes of data, but also generate insights from existing data. These insights help them understand better about their customers and predict market trends. With this initiative, they can take advantage of the cloud platform to achieve this goal because it manages higher data volume, speed and variation. This cloud platform enables them to provide elasticity and efficient computing and storage resources. They also provide many ready-to-use tools for building data analytics in various stages. Additionally, an on-demand pricing model allows organizations to pay for what they consume. It changes the organizational consumption model from capital expenditure to operational expenditure. It greatly minimizes initial capital investment to build data analytics solutions and implement other innovative ideas. This paper highlights the main reasons for encouraging organizations to build data analytics in the cloud. It also shows how to articulate data analytics frameworks for ecommerce platforms in the cloud and how to integrate machine learning models into data analytics processes, to create more sophisticated analyzes. AWS Amazon Web Services' premier public cloud platform is adopted to demonstrate these concepts and practices with real-life business cases.