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CompTIA Data+ Exam (2025) Sample Questions (Q104-Q109):

NEW QUESTION # 104
A data analyst needs to get an accurate idea of how data components are automated. Which of the following types of documentation should the analyst review first?

A. Data dictionary
B. Data lineage
C. Data flow diagram
D. Data explainability report

Answer: C

Explanation:
This question pertains to theData Concepts and Environmentsdomain, focusing on documentation for understanding data processes. The analyst needs to understand automation of data components, which involves data movement and processes.
* Data flow diagram (Option A): A data flow diagram (DFD) visualizes how data moves through systems, including automated processes, making it the best starting point.
* Data explainability report (Option B): This is related to AI/ML model transparency, not data automation.
* Data dictionary (Option C): A data dictionary defines data elements, not how they're automated.
* Data lineage (Option D): Data lineage tracks data origin and transformations but doesn't focus on automation processes.
The DA0-002 Data Concepts and Environments domain includes understanding "data schemas and dimensions," and a data flow diagram is key for visualizing automation.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.

NEW QUESTION # 105
A data analyst needs to remove all duplicate values between two tables, "Employees" and "Managers," using SQL SELECT statements. Which of the following should the analyst use for this task?

A. SELECT * FROM Employees UNION ALL SELECT * FROM Managers
B. SELECT * FROM Employees UNION SELECT * FROM Managers
C. SELECT * FROM Employees CROSS JOIN SELECT * FROM Managers
D. SELECT * FROM Employees JOIN SELECT * FROM Managers

Answer: B

Explanation:
This question pertains to theData Acquisition and Preparationdomain, focusing on combining and deduplicating data using SQL. The task is to remove duplicates between two tables, meaning the analyst needs a unique set of records from both.
* SELECT * FROM Employees UNION ALL SELECT * FROM Managers (Option A): UNION ALL combines all rows from both tables, including duplicates, which doesn't meet the requirement.
* SELECT * FROM Employees UNION SELECT * FROM Managers (Option B): UNION combines rows from both tables and automatically removes duplicates, providing a unique set of records, which fits the task.
* SELECT * FROM Employees JOIN SELECT * FROM Managers (Option C): This syntax is incorrect; a JOIN requires an ON clause, and it wouldn't remove duplicates.
* SELECT * FROM Employees CROSS JOIN SELECT * FROM Managers (Option D): A CROSS JOIN creates a Cartesian product, resulting in all possible combinations, not removing duplicates.
The DA0-002 Data Acquisition and Preparation domain includes "executing data manipulation," and UNION is the correct SQL operation for combining tables while removing duplicates.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 2.0 Data Acquisition and Preparation.

NEW QUESTION # 106
A product goes viral on social media, creating high demand. Distribution channels are facing supply chain issues because the testing and training models that are used for sales forecasting have not encountered similar demand. Which of the following best describes this situation?

A. Model bias
B. Incorrect sizing
C. Data drift
D. Skewing

Answer: C

Explanation:
This question pertains to theData Analysisdomain, focusing on issues with forecasting models. The scenario describes a sudden change in demand (viral product) that the model couldn't predict because it hasn't seen similar patterns before.
* Model bias (Option A): Model bias occurs when a model systematically favors certain outcomes due to flawed training data, but this scenario is about a change in data patterns, not bias.
* Data drift (Option B): Data drift occurs when the statistical properties of the data change over time (e.
g., sudden high demand due to virality), causing the model to perform poorly because it was trained on different patterns, which fits the scenario.
* Incorrect sizing (Option C): This term is vague and not a standard concept in data analysis for this context.
* Skewing (Option D): Skewing refers to data distribution asymmetry, not a change in data patterns affecting model performance.
The DA0-002 Data Analysis domain includes understanding "applying the appropriate descriptive statistical methods," and data drift is a key concept in forecasting when data patterns change unexpectedly.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.

NEW QUESTION # 107
A data analyst receives the following sales data for a convenience store:
Item
Quantity
Price
Chocolate Bars
7
$1.99
Vanilla Ice Bars
2
$4.99
Chocolate Wafers
6
$0.99
Peanut Butter
2
$2.99
Cups
3
$4.99
Strawberry Jam
3
$4.99
Chocolate Cake
9
$6.99
Milk Chocolate
2
$2.99
Almonds
5
$2.99
The analyst needs to provide information on the products that contain chocolate. Which of the following RegEx should the analyst use to filter the chocolate products?

A. Chocolate!
B. #Chocolate#$
C. %Chocolate&
D. Chocolate$

Answer: D

Explanation:
This question falls under theData Acquisition and Preparationdomain, which includes techniques for manipulating and filtering data, such as using regular expressions (RegEx) to identify specific patterns in text data. The task is to filter items containing the word "Chocolate."
* Chocolate! (Option A): In RegEx, "!" is not a valid pattern for matching a word like "Chocolate." It typically denotes negation in some contexts, but here it's incorrect.
* Chocolate$ (Option B): The "$" in RegEx anchors the pattern to the end of the string, meaning it matches "Chocolate" at the end of an item name (e.g., "Milk Chocolate"). This is the most appropriate pattern for identifying items ending with "Chocolate," which applies to the relevant items in the list.
* %Chocolate& (Option C): "%" and "&" are not standard RegEx anchors; they're often used in SQL LIKE patterns, not RegEx, making this incorrect.
* #Chocolate#$ (Option D): "#" is not a standard RegEx anchor, and this pattern would look for
"Chocolate" surrounded by "#", which doesn't match the data.
The DA0-002 Data Acquisition and Preparation domain includes "executing data manipulation" , and RegEx is a common technique for filtering text data. The pattern "Chocolate$" correctly identifies items like
"Chocolate Bars," "Chocolate Wafers," "Chocolate Cake," and "Milk Chocolate." Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 2.0 Data Acquisition and Preparation

NEW QUESTION # 108
Which of the following best enables the retrieval and manipulation of data that is stored in a relational database?

A. SQL
B. XML
C. JavaScript
D. Excel

Answer: A

Explanation:
This question pertains to theData Concepts and Environmentsdomain, focusing on tools for interacting with relational databases. The task is to identify the best method for retrieving and manipulating data.
* XML (Option A): XML is a data format, not a language for retrieving or manipulating database data.
* SQL (Option B): SQL (Structured Query Language) is specifically designed for querying and manipulating data in relational databases (e.g., SELECT, UPDATE), making it the best choice.
* Excel (Option C): Excel can analyze data but isn't designed for direct database manipulation.
* JavaScript (Option D): JavaScript is a programming language for web development, not optimized for relational database operations.
The DA0-002 Data Concepts and Environments domain includes understanding "different types of databases," and SQL is the standard language for relational database operations.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.

NEW QUESTION # 109
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Use CompTIA Data+ Exam (2025) sure pass guide dumps to pass CompTIA Data+ Exam (2025) actual test

Practice DA0-002 Test Online, DA0-002 Examcollection Questions Answers

CompTIA Data+ Exam (2025) Sample Questions (Q104-Q109):

Updated DA0-002 CBT 100% Pass | Latest Practice DA0-002 Test Online: CompTIA Data+ Exam (2025)

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