What are some effective flattening techniques in data analytics?
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What are some effective flattening techniques in data analytics?
Flattening techniques in data analytics help simplify complex data structures. Common methods include normalization, denormalization, and pivoting.
Can you explain normalization and when to use it?
Normalization is the process of organizing data to reduce redundancy. It's best used when you want to ensure data integrity and efficiency in queries.
What about denormalization? How does it differ?
Denormalization involves combining tables to improve read performance. It's useful in scenarios where read speed is prioritized over write speed.
Are there any tools that can help with these techniques?
Yes, tools like SQL databases, Pandas in Python, and ETL tools can assist in applying these flattening techniques effectively.
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