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[General] DA0-002 Valid Braindumps Book | Valid DA0-002 Exam Objectives

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【General】 DA0-002 Valid Braindumps Book | Valid DA0-002 Exam Objectives

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CompTIA Data+ Exam (2025) Sample Questions (Q115-Q120):NEW QUESTION # 115
A data analyst needs to create a combined report that includes information from the following two tables:
Managers table
ID
First_name
Last_name
Job_title
1001
John
Doe
Manager
1002
Jane
Roe
Director
Non-managers table
ID
First_name
Last_name
Job_title
1003
Robert
Roe
Business Analyst
1004
Jane
Doe
Sales Representative
1005
John
Roe
Operations Analyst
Which of the following query methods should the analyst use for this task?
  • A. Nested
  • B. Group
  • C. Union
  • D. Join
Answer: C
Explanation:
This question pertains to theData Acquisition and Preparationdomain, focusing on combining data from two tables. Both tables have the same structure (ID, First_name, Last_name, Job_title) and contain employee data, suggesting the task is to create a single list of all employees.
* Group (Option A): Grouping (e.g., GROUP BY in SQL) is for aggregation (e.g., counting employees by job title), not combining tables into a single report.
* Join (Option B): Joining tables (e.g., INNER JOIN) requires a common key and combines tables horizontally, but there's no indication of a relationship between the tables (e.g., no shared key beyond ID, which isn't linked).
* Union (Option C): UNION combines the rows of two tables with the same structure into a single result set, removing duplicates, which is ideal for creating a combined report of all employees from both tables.
* Nested (Option D): Nested queries (e.g., subqueries) are used for complex filtering, not for combining tables into a single list.
The DA0-002 Data Acquisition and Preparation domain includes "executing data manipulation," and UNION is the best method for combining two tables with identical structures into a single report.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 2.0 Data Acquisition and Preparation.

NEW QUESTION # 116
A data analyst calculated the average score per student without making any changes to the following table:
Student
Subject
Score
123
Math
100
123
Biology
80
234
Math
96
123
Biology
80
345
Biology
88
234
Math
96
Which of the following exploration techniques should the analyst have considered before calculating the average?
  • A. Grouping
  • B. Redundancy
  • C. Binning
  • D. Duplication
Answer: D
Explanation:
This question pertains to theData Governancedomain, focusing on data quality issues that affect analysis.
The table contains duplicate rows, which would skew the average score calculation if not addressed.
* Student 123: Math (100), Biology (80), Biology (80)- Duplicate Biology score.
* Student 234: Math (96), Math (96)- Duplicate Math score.
* Student 345: Biology (88)- No duplicates.
* Duplication (Option A): The table has duplicate rows (e.g., Student 123's Biology score of 80 appears twice), which would inflate the average if not removed. The analyst should have checked for duplicates before calculating the average.
* Redundancy (Option B): Redundancy refers to unnecessary fields (e.g., storing the same data in multiple columns), not duplicate rows.
* Binning (Option C): Binning groups data into categories, not relevant for addressing duplicates in averaging.
* Grouping (Option D): Grouping (e.g., GROUP BY in SQL) might be part of the solution,but the issue to identify is duplication.
The DA0-002 Data Governance domain includes "data quality control concepts," and checking for duplication is critical to ensure accurate calculations like averages.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.

NEW QUESTION # 117
Which of the following tables holds relational keys and numeric values?
  • A. Transactional
  • B. Graph
  • C. Fact
  • D. Dimensional
Answer: C
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 # 118
A data analyst receives an email from the IT department about renewing the company password, and the analyst follows the password reset link as required. Later in the week, the analyst receives the following notification when running a recurring analysis that connects to the database:
Log-in failed for user '<username>'
Which of the following is most likely the reason for this issue?
  • A. The company changed its database authentication method.
  • B. The analyst did not change the password used to launch the report.
  • C. The password expiration process locked the account.
  • D. The company is experiencing issues with password replication.
Answer: B
Explanation:
This question falls under theData Governancedomain, focusing on data access and security troubleshooting.
The analyst reset their password, but the recurring analysis failed to log in, indicating a mismatch.
* The company changed its database authentication method (Option A): This would affect all users, not just the analyst, and there's no indication of a broader change.
* The password expiration process locked the account (Option B): The analyst reset the password as required, so the account isn't likely locked due to expiration.
* The analyst did not change the password used to launch the report (Option C): Recurring analyses often use stored credentials. If the analyst updated their password but didn't update the stored credentials for the analysis, the login would fail, making this the most likely reason.
* The company is experiencing issues with password replication (Option D): This is possible but less likely without evidence of broader system issues.
The DA0-002 Data Governance domain includes "data privacy concepts," and ensuring stored credentials match updated passwords is a common issue in recurring analyses.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.

NEW QUESTION # 119
A data analyst is creating a new dataset that involves bringing together the following datasets:
Name
ID
Date of birth
Frank
23525
3/19
Martha
11290
6/13
Ellen
12141
11/4
ID
Address
City
State
23525
1234 Harding
Chicago
IL
11040
935 Terrace Hills
Chino
CA
11290
2 Speedway
Miami
FL
Which of the following would be the output if the data analyst does a FULL JOIN?
  • A. Name
    ID
    Date of birth
    Address
    City
    State
    Frank
    23525
    3/19
    1234 Harding
    Chicago
    IL
    Martha
    11290
    6/13
    2 Speedway
    Miami
    FL
    Ellen
    12141
    11/4
    935 Terrace Hills
    Chino
    CA
  • B. Name
    ID
    Date of birth
    Address
    City
    State
    Frank
    23525
    3/19
    1234 Harding
    Chicago
    IL
    Martha
    11290
    6/13
    935 Terrace Hills
    Chino
    CA
    Ellen
    12141
    11/4
    2 Speedway
    Miami
    FL
  • C. Name
    ID
    Date of birth
    Address
    City
    State
    Frank
    23525
    3/19
    1234 Harding
    Chicago
    IL
    Martha
    11290
    6/13
    2 Speedway
    Miami
    FL
    Ellen
    12141
    11/4
    11040
    935 Terrace Hills
    Chino
    CA
  • D. Name
    ID
    Date of birth
    Address
    City
    State
    Frank
    23525
    3/19
    1234 Harding
    Chicago
    IL
    Martha
    11290
    6/13
    935 Terrace Hills
    Chino
    CA
    Ellen
    12141
    11/4
    2 Speedway
    Miami
    FL
Answer: C
Explanation:
This question falls under theData Concepts and Environmentsdomain, focusing on database operations like joins. A FULL JOIN combines all rows from both tables, including matches and non-matches, filling in NULLs where there's no corresponding data.
* The first table has IDs: 23525 (Frank), 11290 (Martha), 12141 (Ellen).
* The second table has IDs: 23525, 11040, 11290.
* A FULL JOIN includes all IDs: 23525, 11290, 12141, 11040.
* 23525 matches (Frank with 1234 Harding, Chicago, IL).
* 11290 matches (Martha with 2 Speedway, Miami, FL).
* 12141 has no match in the second table, so Address, City, and State are NULL.
* 11040 has no match in the first table, so Name and Date of birth are NULL.
* Option A: Incorrect; it includes a row for Ellen with "2 Speedway," but Ellen's ID (12141) doesn't match any address, and 11040 is missing.
* Option B: Identical to Option A, so incorrect for the same reasons.
* Option C: Incorrect; it mismatches addresses (e.g., Ellen with 935 Terrace Hills, which belongs to
11040).
* Option D: Correct; it includes all IDs, with NULLs for non-matching rows (Ellen has no address, and
11040 has no name).
The DA0-002 Data Concepts and Environments domain includes understanding "data schemas and dimensions," such as performing joins in relational databases.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.

NEW QUESTION # 120
......
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