DA0-002 ACTUAL EXAM, VALID DUMPS DA0-002 QUESTIONS

DA0-002 Actual Exam, Valid Dumps DA0-002 Questions

DA0-002 Actual Exam, Valid Dumps DA0-002 Questions

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CompTIA Data+ Exam (2025) Sample Questions (Q67-Q72):

NEW QUESTION # 67
Which of the following tables holds relational keys and numeric values?

  • A. Fact
  • B. Graph
  • C. Dimensional
  • D. Transactional

Answer: A

Explanation:
This question falls under theData Concepts and Environmentsdomain, focusing on understanding table types in data warehousing. The task is to identify a table that holds relational keys and numeric values, typically used in a star schema.
* Fact (Option A): Fact tables in a star schema store quantitative data (numeric values, e.g., sales amounts) and foreign keys (relational keys) linking to dimension tables, making this the correct choice.
* Graph (Option B): Graph tables are used in graph databases for relationships (e.g., nodes, edges), not typically for relational keys and numeric values in a traditional sense.
* Dimensional (Option C): Dimension tables store descriptive attributes (e.g., product names) and primary keys, not typically numeric measures.
* Transactional (Option D): Transactional tables are used in OLTP systems and may contain numeric values, but they're not specifically designed for relational keys in a data warehousing context.
The DA0-002 Data Concepts and Environments domain includes understanding "data schemas and dimensions," and fact tables are designed to hold relational keys and numeric values in a data warehouse.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.


NEW QUESTION # 68
Which of the following is the most efficient to use when programming repeatable tasks?

  • A. LLM
  • B. Deep learning
  • C. RPA
  • D. NLP

Answer: C

Explanation:
This question pertains to theData Acquisition and Preparationdomain, focusing on tools for automating repeatable tasks in data processes. The task is to identify the most efficient programming method.
* LLM (Option A): Large Language Models (e.g., GPT) are for text generation, not efficient for repeatable data tasks.
* Deep learning (Option B): Deep learning is for complex pattern recognition (e.g., image classification), not efficient for simple repeatable tasks.
* NLP (Option C): Natural Language Processing is for text analysis, not general repeatable tasks.
* RPA (Option D): Robotic Process Automation (RPA) automates repetitive, rule-based tasks (e.g., data entry, file processing), making it the most efficient for programming repeatable tasks.
The DA0-002 Data Acquisition and Preparation domain includes "executing data manipulation," and RPA is a widely used method for automating repeatable data tasks.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 2.0 Data Acquisition and Preparation.


NEW QUESTION # 69
A data analyst is joining two tables with different content and one common field. Which of the following should the analyst do to most efficiently meet this requirement?

  • A. Create a cluster to facilitate data integration between the tables.
  • B. Append the values of the matching columns and concatenate the other data fields.
  • C. Match the records of the related columns and merge the tables.
  • D. Explode both tables to identify unique values and reorder the fields in one table.

Answer: C

Explanation:
This question falls under theData Acquisition and Preparationdomain, focusing on combining data from multiple tables. The tables have different content but share a common field, indicating a join operation.
* Match the records of the related columns and merge the tables (Option A): This describes a join operation, where records are matched on the common field (e.g., a key like Customer_ID) and the tables are merged, which is the most efficient method.
* Create a cluster to facilitate data integration between the tables (Option B): Clustering is a machine learning technique, not a method for joining tables.
* Explode both tables to identify unique values and reorder the fields in one table (Option C):
Exploding is used in nested data (e.g., JSON arrays), and this approach is overly complex and unnecessary.
* Append the values of the matching columns and concatenate the other data fields (Option D):
Appending stacks tables vertically, and concatenation applies to text, neither of which is appropriate for joining tables with a common field.
The DA0-002 Data Acquisition and Preparation domain includes "executing data manipulation," such as joining tables using a common field.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 2.0 Data Acquisition and Preparation.


NEW QUESTION # 70
A data analyst is evaluating all conditions in a query. Which of the following is the best logical function to accomplish this task?

  • A. OR
  • B. AND
  • C. NOT
  • D. IF

Answer: B

Explanation:
This question falls under theData Analysisdomain, focusing on SQL logical functions for query evaluation.
The task is to evaluate "all conditions," implying multiple conditions must be true together.
* OR (Option A): OR returns true if any condition is true, not ensuring all conditions are met.
* NOT (Option B): NOT negates a condition, not suitable for combining multiple conditions.
* AND (Option C): AND requires all conditions to be true, which aligns with evaluating "allconditions" in a query.
* IF (Option D): IF is a conditional function for decision-making, not for evaluating multiple conditions together.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods using SQL queries," and AND is the best logical function for ensuring all conditions are met.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.


NEW QUESTION # 71
A data analyst wants to use the following tables to find all the customers who have not placed an order:
Customers table
ID
Name
Address
Products table
ID
Name
Customer_ID
Which of the following SQL statements is the best way to accomplish this task?

  • A. SELECT * FROM PRODUCTS AS P INNER JOIN CUSTOMERS AS C ON P.Customer_ID = C.ID WHERE (SELECT COUNT(P.) = 0)
  • B. SELECT * FROM CUSTOMERS AS C INNER JOIN PRODUCTS AS P ON C.ID = C.IDWHERE COUNT(P.) = 0
  • C. SELECT * FROM PRODUCTS AS P LEFT JOIN CUSTOMERS AS C ON P.Customer_ID = C.ID WHERE P.Customer_ID IS NOT NULL
  • D. SELECT * FROM CUSTOMERS AS C LEFT JOIN PRODUCTS AS P ON C.ID = P.Customer_ID WHERE P.Customer_ID IS NULL

Answer: D

Explanation:
This question pertains to theData Analysisdomain, focusing on SQL queries to analyze data relationships.
The task is to find customers who have not placed an order, meaning customers in the Customers table without a matching Customer_ID in the Products table.
* Option A: SELECT * FROM CUSTOMERS AS C LEFT JOIN PRODUCTS AS P ON C.ID = P.
Customer_ID WHERE P.Customer_ID IS NULLA LEFT JOIN includes all customers, even those without orders (where Products columns are NULL). Filtering with WHERE P.Customer_ID IS NULL selects only customers without a match in Products, correctly identifying those who haven't ordered.
* Option B: SELECT * FROM CUSTOMERS AS C INNER JOIN PRODUCTS AS P ON C.ID = C.
ID WHERE COUNT(P.*) = 0An INNER JOIN only includes matching records, so it won't return customers without orders. The join condition C.ID = C.ID is also incorrect, and COUNT requires a GROUP BY, making this invalid.
* Option C: SELECT * FROM PRODUCTS AS P INNER JOIN CUSTOMERS AS C ON P.
Customer_ID = C.ID WHERE (SELECT COUNT(P.*) = 0)An INNER JOIN excludes customers without orders, and the subquery syntax is incorrect (COUNT needs a GROUP BY or to be part of a HAVING clause).
* Option D: SELECT * FROM PRODUCTS AS P LEFT JOIN CUSTOMERS AS C ON P.
Customer_ID = C.ID WHERE P.Customer_ID IS NOT NULLThis starts with Products and joins Customers, returning only records with orders (opposite of the task), and IS NOT NULL further excludes non-ordering customers.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods using SQL queries," and a LEFT JOIN with a NULL check is the standard method for finding non-matching records.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.


NEW QUESTION # 72
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