What Two Steps Are Performed During the Data Validation Process?

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You should easily be able to demonstrate to your interviewer that you know and understand these steps, so be prepared for this question if you are asked. Be sure to not only answer with the two different steps—data validation and data verification—but also how they are performed.

During the data validation process in data analytics, two key steps are typically performed:

  1. Data Cleaning: This step involves identifying and correcting errors or inconsistencies in the data. It may include removing duplicate entries, handling missing values, correcting formatting issues, and resolving inconsistencies in the data.
  2. Data Verification: Once the data is cleaned, it undergoes verification to ensure its accuracy and reliability. This step involves comparing the cleaned data against predefined rules, business logic, or statistical analysis to validate its integrity. Verification may also involve cross-referencing with external data sources or performing validation checks to confirm that the data meets specific criteria or expectations.

These two steps are essential in ensuring that the data used for analysis is accurate, reliable, and suitable for making informed business decisions.