DA0-002 Question #4: Real Exam Question with Answer & Explanation

The correct answer is C: Binning. To segment customers based on spending behavior from a large dataset, binning is an effective technique to group continuous spending amounts into discrete categories or ranges. This simplifies the data for analysis and segmentation.

Data Acquisition and Preparation

Question

A data analyst team needs to segment customers based on customer spending behavior. Given one million rows of data like the information in the following sales order table: Which of the following techniques should the team use for this task?

Options

AStandardization
BConcatenate
CBinning
DAppending

Explanation

To segment customers based on spending behavior from a large dataset, binning is an effective technique to group continuous spending amounts into discrete categories or ranges. This simplifies the data for analysis and segmentation.

Common mistakes.

A. Standardization (e.g., z-score normalization) transforms data to have a common scale but does not directly segment or categorize data into groups like spending tiers.
B. Concatenation combines strings or fields, which is not relevant for segmenting numerical customer spending data.
D. Appending combines rows of similarly structured datasets, which is for data consolidation, not for segmenting existing data within a single table.

Concept tested. Data binning, data segmentation

Reference. https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.KBinsDiscretizer.html

Topics

#Customer Segmentation#Data Binning#Data Preparation#Numerical Data Transformation

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