When should I use real data in my projects?

When should I use real data in my projects?

Using real data is crucial when accuracy is essential, such as in predictive modeling or user behavior analysis.

Are there situations where synthetic data is better?

Yes, synthetic data can be useful for testing, training models without privacy concerns, or when real data is scarce.

How do I ensure the quality of real data?

To ensure quality, validate data sources, check for consistency, and perform regular audits to identify anomalies.

What are the risks of using real data?

Risks include privacy issues, data breaches, and potential biases in the data that can affect outcomes.