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CS Professional · Artificial Intelligence, Data Analytics and Cyber Security - Laws and Practice · Data Analytics

An analyst at a Pune logistics firm finds that 8% of delivery records have missing pin codes and some duplicate shipment IDs. Before any model is built, which lifecycle activity addresses this?

Data preparation, meaning cleaning and preprocessing, addresses missing pin codes and duplicate IDs. These quality defects must be fixed before modelling, because validation, reporting and archival happen later and cannot correct flawed input data.

  1. AData preparation (cleaning and preprocessing)Correct
  2. BModel validation on test data
  3. CInsight communication to the board
  4. DArchival of final reports

Explanation

Missing values and duplicates are data quality defects handled in data preparation, which precedes modelling. Model validation checks predictive performance after a model exists, and communication and archival come at the end. So cleaning and preprocessing is the correct activity.

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