You are working on a machine learning project that requires training models on a large dataset. Which of the following steps should you take to ensure the data quality of the dataset used for training?

Simulated

Perform data sampling to identify any missing or inconsistent data points and then manually correct them before training the models.

14.3%

Use a data profiling tool to analyze the dataset and identify any anomalies or inconsistencies in the data before training the models.

0.0%

Assume that the dataset is of high quality and train the models without any data validation or profiling.

0.0%

Implement a data validation process that checks for data completeness, consistency, accuracy, and integrity before training the models.

85.7%

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