How can you use different data warehouse architectures to improve your data engineering?

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Data engineering is the process of designing, building, and maintaining data pipelines, systems, and platforms that enable data analysis, reporting, and machine learning. One of the key components of data engineering is data warehousing, which is the practice of storing and organizing data from various sources in a centralized and structured way. Data warehouse architectures are the models or frameworks that define how data is stored, accessed, and processed in a data warehouse. In this article, you will learn about some of the common data warehouse architectures and how they can help you improve your data engineering.

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