DA Data Cleaning and Preparation 2

Question 1

What is data parsing in the context of data preparation?

Accepted Answer

Extracting structured information from raw or unstructured text

Answer

Parsing breaks down raw data (like strings or JSON) into structured, usable components for analysis.

Question 2

Which technique rescales data so the mean is 0 and standard deviation is 1?

Accepted Answer

Standardization (Z-score scaling)

Answer

Standardization subtracts the mean and divides by the standard deviation, centering the data at zero with unit variance.

Question 3

What is the purpose of data profiling?

Accepted Answer

Assessing data quality, structure, and content before analysis

Answer

Data profiling examines datasets to understand their structure, completeness, distributions, and anomalies before analysis begins.

Question 4

What is binning (bucketing) in data preparation?

Accepted Answer

Grouping continuous values into discrete categories or intervals

Answer

Binning converts continuous numeric values into categorical bins, which can reduce noise and simplify analysis.

Question 5

What is a regex (regular expression) commonly used for in data cleaning?

Accepted Answer

Pattern-based text extraction, validation, and replacement

Answer

Regular expressions define patterns that match character sequences, enabling extraction, validation, or replacement of text in data fields.

DA - Data Analyst Practice Test