What is the difference between data normalization and flattening?
An example of an AI chatbot conversation about data normalization vs flattening.
What is the difference between data normalization and flattening?
Data normalization is the process of organizing data to reduce redundancy, while flattening involves converting nested data structures into a single level.
Can you give me an example of when to use normalization?
Sure! Normalization is often used in relational databases to ensure data integrity and eliminate duplicate entries.
And when would I use flattening instead?
Flattening is useful when you need to prepare data for analysis or visualization, especially when dealing with nested JSON objects.
Are there any downsides to either method?
Yes, normalization can lead to complex queries, while flattening can result in data loss if not done carefully.
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