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easyData Analyst interview question

You receive a new dataset from a client. What steps do you take to clean it before analysis?

What the interviewer wants to hear

  • Understand columns, grain and source first
  • Check and handle missing values
  • Remove or investigate duplicates
  • Fix data types and inconsistent formats
  • Look for outliers and impossible values
  • Document every change

Model answer

First I understand the data: what one row represents, where it came from and what each column means. Then I profile it: row counts, missing values per column, distinct values and min and max. I check for duplicates on the key that should be unique and find out why they exist before deleting anything. I fix data types, such as dates stored as text or numbers with commas, and standardise formats like city names written in different ways. I look for outliers and impossible values, like negative ages or future order dates, and decide with the business whether they are errors. For missing values I choose based on context: drop, fill with median, or flag them. Finally I document every step, ideally in a script or notebook, so the cleaning is repeatable and someone else can check it.

Can you answer it under time pressure?

Take a timed easy round and get scored on every answer.

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