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CompTIA DA0-002 Exam Overview:

Certification Vendor:CompTIA
Exam Name:CompTIA Data+ Certification Exam
Exam Number:DA0-002
Exam Format:Multiple-response, Multiple-choice, Performance-based questions
Available Languages:English
Passing Score:675 (on a scale of 100โ€“900)
Exam Price:$253 USD (may vary by region/tax)
Exam Duration:90 minutes
Certificate Validity Period:3 years
Real Exam Qty:Up to 90
Recommended Training:CompTIA CertMaster Learn for Data+
CompTIA Data+ Study Resources
Exam Registration:CompTIA Data+ Certification Page
Pearson VUE CompTIA Exams Registration
Sample Questions:CompTIA DA0-002 Sample Questions
Exam Way:Delivered via Pearson VUE testing centers or online proctored exam
Pre Condition:No mandatory prerequisites. Recommended: 18โ€“24 months of experience in a business/data analytics environment.
Official Syllabus URL:https://www.comptia.org/certifications/data-plus

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CompTIA DA0-002 Exam Syllabus Topics:

TopicDetails
Topic 1
  • 5.0 Data Governance, Quality, and Controls
Topic 2
  • Data Concepts and Environments: This section of the exam measures the skills of a Junior Data Analyst and focuses on understanding core data concepts such as database types, schema structures, and data formats. It highlights differences between structured and unstructured data, compares file types like CSV, JSON, and XML, and introduces key ideas about data dimensions and slowly changing dimensions. Knowing how data is stored and organized helps professionals better prepare for analysis and reporting tasks.
Topic 3
  • Visualization: This section of the exam measures skills of a Data Visualisation Specialist and focuses on turning raw data into clear, visual insights. It teaches how to match visual formats like bar charts, heat maps, and line graphs to specific audiences and needs. Candidates must understand how to create dashboards and reports using proper design elements such as labels, layout, branding, and colour schemes. This section also includes best practices for dashboard development and delivery through various platforms and user access levels.

CompTIA Data+ Exam Sample Questions (Q191-Q196):

NEW QUESTION # 191
A data analyst receives four files that need to be unified into a single spreadsheet for further analysis. All of the files have the same structure, number of columns, and field names, but each file contains different values.
Which of the following methods will help the analyst convert the files into a single spreadsheet?

Answer: D

Explanation:
This question is part of theData Acquisition and Preparationdomain, which involves combining data from multiple sources. The files have the same structure but different values, meaning theyneed to be stacked vertically into one dataset.
* Merging (Option A): Merging typically involves joining datasets on a common key (e.g., a customer ID), which isn't indicated here since the files only differ in values, not keys.
* Appending (Option B): Appending stacks datasets vertically, combining rows from files with the same structure into a single dataset, which matches the scenario.
* Parsing (Option C): Parsing involves breaking down data (e.g., splitting text), not combining files.
* Clustering (Option D): Clustering is a machine learning technique for grouping similar data points, not for combining files.
The DA0-002 Data Acquisition and Preparation domain includes "executing data manipulation," such as appending datasets with identical structures.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 2.0 Data Acquisition and Preparation.


NEW QUESTION # 192
A data analyst is working on an initial analysis of the dataset in the following table:

Which of the following issues should the analyst flag in the data report?

Answer: A

Explanation:
The value 245 is significantly higher than the other counts, indicating an outlier that should be flagged for further investigation.


NEW QUESTION # 193
An engineer needs to build an ETL process to calculate the average sales of individual stores.
Each store sends their sales data as .csv files. Which of the following would the engineer most likely do to the data?

Answer: A

Explanation:
Because each store provides sales data as CSV files, the engineer must first parse the files to extract and structure the data into usable datasets. This step is necessary before the ETL process can aggregate the sales data and calculate average sales for individual stores.


NEW QUESTION # 194
A company reports on seven years of data in a sales dashboard. The dashboard pulls from a sales database that has 30 years of data. The dashboard performance is slow. Which of the following is the best way to improve the dashboard's performance?

Answer: C

Explanation:
This question falls under theData Governancedomain, focusing on optimizing data quality and performance in dashboards. The dashboard is slow because it pulls from a large database (30 years) but only needs seven years of data.
* Performing a code review (Option A): A code review might identify inefficiencies, but it's not the most direct solution for this scenario.
* Checking network connectivity (Option B): Network issues might cause delays, but the primary issue is the data volume, not connectivity.
* Filtering to include only relevant data (Option C): Filtering the data to include only the last seven years reduces the dataset size, directly improving performance by minimizing the data processed.
* Adding more RAM and rerunning (Option D): Adding RAM might help, but it's a hardware solution that doesn't address the root cause of excessive data.
The DA0-002 Data Governance domain includes "data quality control concepts," such as optimizing performance by filtering data to improve efficiency.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.


NEW QUESTION # 195
Which of the following best represents a type of infrastructure that requires a company to purchase and maintain all of its own servers?

Answer: A

Explanation:
A private infrastructure requires the organization to own, manage, and maintain its own servers and hardware, unlike cloud or hybrid models where resources are shared or hosted externally.


NEW QUESTION # 196
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