A healthcare data analyst is working with data sets containing patient information, medical records, and metrics. The data analyst needs to combine two data sets that have a common field…

The correct answer is D. Data merge. A data merge combines two or more datasets based on a shared key field - in this case, Patient_ID. The result is a unified dataset where matching records are joined together. Data blending also combines sources but is typically used in BI tools and does not require a formal…

Data Analysis

Question

A healthcare data analyst is working with data sets containing patient information, medical records, and metrics. The data analyst needs to combine two data sets that have a common field, Patient_ID. Which of the following data manipulation techniques should the analyst use?

Options

AData blending
BConcatenation
CData append
DData merge

How the community answered

(23 responses)

B
4% (1)
D
96% (22)

Explanation

A data merge combines two or more datasets based on a shared key field - in this case, Patient_ID. The result is a unified dataset where matching records are joined together. Data blending also combines sources but is typically used in BI tools and does not require a formal key-based join. Concatenation stacks datasets vertically (adds rows) without matching on a key. Data append also adds rows from one dataset to another but does not align records by a common field.

Topics

#Data manipulation#Data integration#Merge operations#Common key

Community Discussion

No community discussion yet for this question.

Full DA0-001 Practice