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[General] Examinations DA0-002 Actual Questions & New DA0-002 Test Topics

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【General】 Examinations DA0-002 Actual Questions & New DA0-002 Test Topics

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CompTIA Data+ Exam (2025) Sample Questions (Q57-Q62):NEW QUESTION # 57
A manager wants a report that contains the days off for each direct report. The manager needs this report to always be up-to-date with the latest data. Which of the following describes the refresh frequency that the manager is requesting?
  • A. Dynamic
  • B. Snapshot
  • C. Ad hoc
  • D. Real-time
Answer: D
Explanation:
This question pertains to the Visualization and Reporting domain, focusing on report refresh frequencies.
The manager needs the report to always be up-to-date, implying continuous data updates.
* Real-time (Option A): Real-time refresh frequency ensures the report reflects the latest data as soon as it changes, which matches the requirement to "always be up-to-date."
* Ad hoc (Option B): Ad hoc reports are generated on-demand, not continuously updated.
* Snapshot (Option C): A snapshot captures data at a specific point in time, not suitable for always being up-to-date.
* Dynamic (Option D): Dynamic reports allow interactivity, but the term doesn't specifically imply real- time updates.
The DA0-002 Visualization and Reporting domain includes "the appropriate visualization in the form of a report" with delivery methods, and real-time refresh frequency ensures the report is always current.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 4.0 Visualization and Reporting.

NEW QUESTION # 58
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. Union
  • B. Nested
  • C. Join
  • D. Group
Answer: A
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 # 59
A recent server migration applied an update to dataset naming conventions. Multiple users are now reporting stale information in an existing dashboard. The date in the dataset confirms a successful data refresh. Which of the following should a data analyst do first?
  • A. Escalate user permissions on the server.
  • B. Filter the data in the dashboard.
  • C. Verify that the dashboard subscription is not expired.
  • D. Confirm the dashboard is pointed to the newest dataset.
Answer: D
Explanation:
This question falls under theData Governancedomain, focusing on troubleshooting data freshness issues in dashboards. The dashboard shows stale data despite a successful refresh, and the server migration updated naming conventions, suggesting a potential mismatch.
* Confirm the dashboard is pointed to the newest dataset (Option A): The server migration updated dataset naming conventions, so the dashboard might still be pointing to an old dataset name, causing stale data. Confirming the dataset connection is the first step.
* Filter the data in the dashboard (Option B): Filtering might adjust the view but doesn't address the root cause of stale data.
* Escalate user permissions on the server (Option C): Permissions issues would likely prevent access, not cause stale data, especially since the dataset refreshed successfully.
* Verify that the dashboard subscription is not expired (Option D): An expired subscription might prevent access, but the dashboard is accessible, just showing stale data.
The DA0-002 Data Governance domain includes "data quality control concepts," such as ensuring dashboards connect to the correct, updated datasets after changes like server migrations.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.

NEW QUESTION # 60
A data analyst pulls a table similar to the following one:
ID
Type
TypeID
Phone
1
Full Time
Full Time 1
Mobile
2
Part Time
Part Time 2
Work
3
Full Time
Full Time 3
Mobile
Which of the following best explains the data issue with TypeID?
  • A. Duplication
  • B. Outlier
  • C. Redundancy
  • D. Missing data
Answer: C
Explanation:
This question is part of theData Concepts and Environmentsdomain, focusing on identifying data quality issues. The table shows Type and TypeID columns, where TypeID seems to repeat information from Type with an additional identifier.
* Redundancy (Option A): The TypeID column (e.g., "Full Time 1") redundantly includes the Type value ("Full Time") with an extra identifier, which is unnecessary and could be simplified by using a numeric ID instead.
* Outlier (Option B): Outliers are data points that deviate significantly, which isn't applicable here.
* Missing data (Option C): There are no missing values in the table.
* Duplication (Option D): Duplication refers to identical rows, but the rows here are unique; the issue is with the column content.
The DA0-002 Data Concepts and Environments domain includes understanding "data schemas and dimensions," and redundancy is a common data quality issue in schema design.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.

NEW QUESTION # 61
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
    935 Terrace Hills
    Chino
    CA
    Ellen
    12141
    11/4
    2 Speedway
    Miami
    FL
  • B. 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
  • 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
    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: B
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 # 62
......
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