Data Analytics Architectures for E-Commerce Platforms in Cloud - Yeung, John; Wong, Simon; Tam, Alvin (International Journal for Applied Information Management, 2021)
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.