Abstract
The demand for data analytics continues to grow as the number of citizen data analysts engaging in analytics activities increases. Data analysis requires a number of complex procedures, all of which can be resource-intensive for analysts to perform manually. This paper compares the technology trends of major cloud-based solutions and discusses automation strategies and technology trends in the cloud environment, with a focus on balancing analytical autonomy and automation, portability of the analytics environment, and improving platform usability. In particular, it compares and analyzes representative platforms such as SageMaker, Vertex AI, and Azure ML to understand the evolution of analytics automation technology and discusses essential components for future advancements. It also discusses how organizations can increase productivity through analytics by using automated platforms for data-driven decision-making.
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