In this 25-minute Data Cleaning Tips interview, you will be discussing your knowledge and experiences in data cleaning and preprocessing. You will be asked to explain the importance of data cleaning in data science and analytics, and to discuss common data quality issues such as missing values, duplicates, and inconsistencies. Your experience with data cleaning tools and libraries, such as Pandas and OpenRefine, will also be explored. Additionally, you will be asked about your techniques for preprocessing data before analysis, including normalization and encoding categorical variables. You will also have the opportunity to share real-world examples of data cleaning challenges you have faced and how you overcame them. Throughout the interview, you will be encouraged to provide specific examples from your data cleaning experiences.

Data Cleaning Tips

Discuss data cleaning and preprocessing