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Data Acquisition and PreparationeasyMultiple ChoiceObjective-mapped

DA0-002 Data Acquisition and Preparation Practice Question

A data analyst is tasked with collecting data from multiple spreadsheets provided by different departments. Each spreadsheet has different column names and formats. What is the best first step?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Develop a data dictionary and standardize column names

Developing a data dictionary and standardizing column names ensures consistency across all data sources before loading, reducing errors and facilitating integration. Immediately loading data can cause inconsistencies. Discarding mismatched data loses potentially valuable information. Using a machine learning model is an unnecessary and complex first step.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Develop a data dictionary and standardize column names

    Why this is correct

    Standardization ensures all data sources align, making subsequent loading and analysis consistent.

  • Discard any mismatched data

    Why it's wrong here

    Discarding data may remove valuable information and is not a best practice.

  • Use a machine learning model to clean data

    Why it's wrong here

    This is too advanced and not the appropriate first step; standardization should be done manually first.

  • Immediately load all data into a database

    Why it's wrong here

    Loading without standardization will lead to inconsistencies and integration issues.

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JA

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This DA0-002 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DA0-002 exam.