Snowflake - Build and Architect Data Pipelines Using AWS - What Is Data-Warehouse?

The video tutorial explains the concept of data warehouses as central repositories for data analysis. It discusses the evolution of data warehousing, highlighting the impact of cloud technology in recent years. The tutorial compares traditional data warehouses with cloud-based solutions, emphasizing the advantages of cloud data warehouses like scalability and distributed processing. It reviews major cloud data warehouse offerings such as Amazon Redshift, Google BigQuery, and Snowflake, and compares Hive and Athena. The video concludes with a preview of future topics related to cloud service providers in data warehousing.

What is a data warehouse and how does it function as a central repository of information?

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How has the evolution of cloud technology impacted data warehousing compared to 20 or 30 years ago?

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What are the main differences between OLTP and OLAP systems in the context of data warehouses?

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Can you name three cloud data warehouse offerings and describe their common characteristics?

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What are some limitations of using Hive on Hadoop and Athena on AWS as cloud data warehouses?

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