Questions

1. What is the aim of data cleaning in the data preparation process?
   1. Accumulating raw data
   2. Transforming data into a masterpiece
   3. Ensuring data is dirty for analysis
   4. Focusing on data quantity over quality
2. Why is it essential to establish a framework and principles for data cleaning efforts?
   1. To speed up the data cleaning process
   2. To prevent a cycle of perpetual data cleaning
   3. To add additional steps in the process of data cleaning
   4. To create more documentation of data
3. What does the process for cleaning data involve?
   1. Data visualization
   2. Data assessment, data profiling, data validation, data cleaning strategies, data transformation, data quality assurance, and documentation
   3. Data storage
   4. Data generation
4. What does data profiling help identify in the data cleaning process?
   1. Patterns, distributions, and outliers
   2. Data storage mechanisms
   3. Data generation techniques
   4. Data transformation errors
5. What is the significance of documenting the data cleaning journey?
   1. It demonstrates the importance...