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[General] 100% Pass Accurate CompTIA - DA0-002 - CompTIA Data+ Exam (2025) Excellect Pass

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【General】 100% Pass Accurate CompTIA - DA0-002 - CompTIA Data+ Exam (2025) Excellect Pass

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CompTIA Data+ Exam (2025) Sample Questions (Q111-Q116):NEW QUESTION # 111
A data analyst must combine service calls into low-, medium-, and high-priority levels in order to analyze organizational responses. Which of the following techniques should the analyst use for this task?
  • A. Augmentation
  • B. Binning
  • C. Imputation
  • D. Scaling
Answer: B
Explanation:
This question pertains to theData Analysisdomain, focusing on techniques for categorizing data. The task involves grouping service calls into priority levels (low, medium, high), which requires segmenting numerical or ordinal data into discrete categories.
* Augmentation (Option A): Augmentation involves adding data (e.g., in machine learning), not categorizing existing data.
* Imputation (Option B): Imputation fills in missing values, not relevant for categorizing priority levels.
* Scaling (Option C): Scaling adjusts numerical data to a common range (e.g., normalization), not suitable for creating priority categories.
* Binning (Option D): Binning groups continuous or ordinal data into discrete categories (e.g., assigning calls to low, medium, or high priority based on a metric like response time), which fits the task.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods," and binning is a standard technique for categorizing data for analysis.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.

NEW QUESTION # 112
A data analyst needs to join together a table data source and web API data source using Python. Which of the following is the best way to accomplish this task?
  • A. Convert the data from the API and database to a string format and convert them to pandas DataFrames that are then merged together.
  • B. Convert the data from the API and database to a JSON format and convert them to pandas DataFrames that are then merged together.
  • C. Convert the data from the API and database to a TXT format and convert them to pandas DataFrames that are then merged together.
  • D. Convert the data from the API and database to a varchar format and convert them to pandas DataFrames that are then merged together.
Answer: B

NEW QUESTION # 113
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
    935 Terrace Hills
    Chino
    CA
    Ellen
    12141
    11/4
    2 Speedway
    Miami
    FL
  • D. 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
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 # 114
Given the following dataset:
Day
Number of Guests
Monday
455
Tuesday
346
Wednesday
382
Thursday
563
Friday
887
Saturday
934
Sunday
346
Which of the following is the mode?
  • A. 0
  • B. 1
  • C. 2
  • D. 3
Answer: A
Explanation:
This question falls under theData Analysisdomain, focusing on statistical measures. The mode is the value that appears most frequently in a dataset.
* Monday: 455
* Tuesday: 346
* Wednesday: 382
* Thursday: 563
* Friday: 887
* Saturday: 934
* Sunday: 346
The value 346 appears twice (Tuesday and Sunday), while all other values (455, 382, 563, 887, 934) appear once. Thus, the mode is 346.
* Option A: 346- Correct, as it's the most frequent value.
* Option B: 446- Incorrect, as 446 doesn't appear in the dataset.
* Option C: 455- Incorrect, as 455 appears only once.
* Option D: 559- Incorrect, as 559 doesn't appear in the dataset.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods," and the mode is a fundamental measure of central tendency.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.

NEW QUESTION # 115
A data analyst is designing a report for the business review team. The team lists the following requirements for the report:
* Specific data points
* Color branding
* Labels and terminology
* Suggested charts and tables
Which of the following components is missing from the requirements?
  • A. Design elements
  • B. Source validation
  • C. Delivery method
  • D. Report type
Answer: C
Explanation:
This question falls under theVisualization and Reportingdomain of CompTIA Data+ DA0-002, which involves understanding the components necessary for designing a report. The given requirements cover data, visuals, and design, but a key aspect of report planning is missing.
* Source validation (Option A): Source validation ensures data accuracy, but it's typically part of the data preparation phase, not a report design requirement.
* Design elements (Option B): Color branding, labels, and terminology are design elements, so this is already included.
* Delivery method (Option C): The delivery method (e.g., recurring, ad hoc, self-service) specifies how the report will be distributed or accessed, which is a critical requirement missing from the list.
* Report type (Option D): Suggested charts and tables imply the report type (e.g., summary, dashboard), so this is indirectly covered.
The DA0-002 Visualization and Reporting domain emphasizes "translating business requirements to form the appropriate visualization," and the delivery method is a key component of report planning that's missing here.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 4.0 Visualization and Reporting.

NEW QUESTION # 116
......
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