What are the differences between data lakes and data warehouses?
An example of an AI chatbot conversation about data lakes and data warehouses.
What are the differences between data lakes and data warehouses?
Data lakes store raw data in its native format, while data warehouses store structured data for analysis.
Can you explain the advantages of using a data lake?
Data lakes allow for flexibility in data storage, support various data types, and enable advanced analytics.
When should I use a data warehouse instead of a data lake?
Use a data warehouse when you need structured data for reporting and business intelligence, ensuring faster query performance.
Are there any scenarios where both are used together?
Yes, many organizations use both to leverage the strengths of each: data lakes for raw data and warehouses for structured analysis.
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