What are some effective data cleanup strategies?
An example of an AI chatbot conversation about data cleanup strategies.
What are some effective data cleanup strategies?
Effective data cleanup strategies include deduplication, normalization, validation, and standardization.
Can you explain deduplication in more detail?
Deduplication involves identifying and removing duplicate records from your dataset to ensure accuracy.
What tools can I use for data normalization?
You can use tools like OpenRefine, Talend, or Python libraries like Pandas for data normalization.
How often should I perform data cleanup?
It's best to perform data cleanup regularly, depending on your data's volatility, at least quarterly.
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