CompTIA Data+ (DA0-002)Data MiningMedium
A data quality specialist is analyzing a dataset of customer addresses. They observe that the 'State' column contains entries like 'California', 'CA', 'california', and 'Cal'. To standardize this column for consistent reporting, which data transformation technique should be applied?
- AData enrichment
- BData aggregation
- CData pivoting
- DData normalization
Show answer & explanationAnswer & explanation
Correct answer: D. Data normalization
Data normalization, in the context of data cleansing, involves standardizing data to a common format or representation, which is precisely what is needed for inconsistent state names.
Why the other options are wrong
- A. Data enrichment adds new information to a dataset, rather than standardizing existing values.
- B. Data aggregation combines multiple rows into a single summary row, not standardizing inconsistent values.
- C. Data pivoting (or unpivoting) reshapes data from rows to columns or vice versa, not for standardization.
Data Normalization (Cleansing)
The process of organizing data in a database to eliminate redundancy and improve data integrity, often involving standardizing inconsistent values to a common format.
- Aims to reduce data redundancy.
- Ensures data consistency and integrity.
- Involves standardizing formats, units, and representations.
Memory trick: Transforming data makes it shine.