Understand the roles, strengths, and trade-offs of Data Lake, Data Warehouse, and Lakehouse architectures.
This deck is for anyone working on architecture related to Data Engineering, from beginner to intermediate.
You will work on points such as: What is the main analytical focus of a data warehouse? · What core role does a lakehouse play in modern analytics? · What is one key difference in data modeling approach between a data l….
1What is the main analytical focus of a data warehouse?
Answer: Supporting consistent, reliable reporting and business analytics on curated data.
2What core role does a lakehouse play in modern analytics?
Answer: Combining low-cost data lake storage with data warehouse-style management and performance.
3What is one key difference in data modeling approach between a data lake and a data warehouse?
Answer: A data lake postpones modeling, while a warehouse models data before loading.
4Compared with a data warehouse, what unique advantage does a lakehouse typically provide?
Answer: Storing diverse data types in open formats while still offering warehouse-like governance.
5In one sentence, what is the primary purpose of a data lake?
Answer: To store large volumes of raw data in its native format for flexible future use.
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