A data analyst is working with a table of retail sales transactions that includes the store's ZIP code for each transaction. To better understand sales performance, the analyst needs to incorporate local demographic data, such as median household income and population density for each ZIP code, from an external public data source. Which data transformation technique does this scenario describe?
The correct answer is Augmentation. Augmentation is the process of adding new data to an existing dataset to enrich it, often by joining it with an external data source. In this scenario, the analyst is adding external demographic data to the internal sales data to provide more context for analysis.
Creating a derived variable is incorrect because it involves generating new data from columns that already exist within the dataset, such as calculating profit from sales and cost columns. It does not involve incorporating external data.
Imputation is incorrect. This technique is used to fill in missing values within a dataset, not to add new features or information from an outside source.
Standardization is a scaling technique used to transform numerical data to have a mean of zero and a standard deviation of one. It does not add new contextual information to the dataset.
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CompTIA Data+ DA0-002 (V2)
Data Acquisition and Preparation
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