Data warehouse & Data lake

🤓 Here are a few examples of less common or more advanced machine learning interview questions related to data warehouse and data lake:

✅Can you explain the difference between a data warehouse and a data lake?

• How do they differ in terms of architecture, data storage, and access?
• Can you give an example of when it would be more appropriate to use a data warehouse versus a data lake?
• How do you decide which one to use for a specific use case?

✅How do you handle data integration in a data warehouse and data lake?

• Can you explain the concepts of ETL and ELT and how they are used in data warehousing and data lakes?
• How do you handle data quality and data governance in a data warehouse and data lake?
• Can you give an example of a data integration project you have worked on and explain the approach you took?

✅How do you perform data modeling in a data warehouse and data lake?

• Can you explain the concept of star and snowflake schemas and how they are used in data warehousing?
• How do you perform data modeling in a data lake?
• Can you give an example of a data modeling project you have worked on and explain the approach you took?

✅How do you handle big data in a data warehouse and data lake?

• Can you explain the concept of distributed computing and how it is used in data warehousing and data lakes?
• How do you handle data partitioning and data compression in a data warehouse and data lake?
• Can you give an example of a big data project you have worked on and explain the approach you took?

✅How do you implement security and access control in a data warehouse and data lake?

• Can you explain the concept of row-level security and how it is used in data warehousing?
• How do you handle data encryption and authentication in a data lake?
• Can you give an example of a security project you have worked on and explain the approach you took?