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| Certification Vendor: | CompTIA |
|---|---|
| Exam Name: | CompTIA Data+ Exam |
| Exam Number: | DA0-002 |
| Certificate Validity Period: | 3 years |
| Exam Format: | Performance-based questions, Multiple-choice |
| Available Languages: | English |
| Passing Score: | 720 (scale 100–900) |
| Exam Price: | $255 USD |
| Real Exam Qty: | Up to 90 |
| Exam Duration: | 90 minutes |
| Recommended Training: | CompTIA Official Training |
| Exam Registration: | Pearson VUE Testing CompTIA Official Registration |
| Sample Questions: | CompTIA DA0-002 Sample Questions |
| Exam Way: | Online proctored or onsite at Pearson VUE test centers |
| Pre Condition: | Recommended 18–24 months of experience in data/business analysis role; familiarity with databases, analytical tools, basic statistics, and visualization |
| Official Syllabus URL: | https://www.comptia.org/certifications/data |
These DA0-002 exam question formats contain real, valid, and updated CompTIA DA0-002 exam questions that will assist you in CompTIA CompTIA Data+ Exam exam preparation and enable you to pass the challenging CompTIA DA0-002 Exam with good scores. The CompTIA DA0-002 questions are prepared by highly experienced professionals and, thus, are kept to the point and concise.
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NEW QUESTION # 132
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?
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 # 133
An analyst needs to produce a final dataset using the following tables:
The expected output should be formatted as follows:
| CourseID | SectionNumber | StudentID | FirstName | LastName |
Which of the following actions is the best way to produce the requested output?
Answer: A
NEW QUESTION # 134
Given the following tables:
Individual table
ID
FirstName
LastName
1
John
Doe
Output
ID
FullName
1
JohnDoe
Which of the following is the best option to display output from FirstName and LastName as FullName?
Answer: C
Explanation:
This question falls under theData Acquisition and Preparationdomain of CompTIA Data+ DA0-002, focusing on data manipulation techniques. The task is to combine FirstName and LastName into a single FullName field (e.g., "JohnDoe").
* Concatenate (Option A): Concatenation combines two or more strings into one (e.g., usingCONCAT in SQL or "+" in Python), which is the correct method to create FullName from FirstName and LastName.
* Filter (Option B): Filtering selects specific rows based on conditions, not suitable for combining fields.
* Join (Option C): Joining combines data from multiple tables, but the task involves manipulating data within a single table.
* Group (Option D): Grouping (e.g., GROUP BY in SQL) is for aggregation, not for combining fields into a new column.
The DA0-002 Data Acquisition and Preparation domain includes "executing data manipulation," and concatenation is the standard technique for combining fields like FirstName and LastName into FullName.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 2.0 Data Acquisition and Preparation.
NEW QUESTION # 135
A data analyst creates a report that identifies the middle 50% of the collected data. Which of the following best describes the analyst's findings?
Answer: D
Explanation:
This question pertains to theData Analysisdomain, focusing on statistical measures. The middle 50% of a dataset refers to a specific statistical concept related to data distribution.
* Interquartile range (Option A): The interquartile range (IQR) is the range between the first quartile (Q1, 25th percentile) and the third quartile (Q3, 75th percentile), representing the middle 50% of the data, which matches the description.
* The difference between mode and median (Option B): This measures the spread between two central tendency metrics but doesn't represent the middle 50% of the data.
* Mean variance (Option C): Variance measures data dispersion around the mean, not the middle 50%.
* Skewness from the slope (Option D): Skewness measures data asymmetry, and "slope" is irrelevant here.
The DA0-002 Data Analysis domain includes "applying the appropriate descriptive statistical methods," and the IQR is the standard measure for the middle 50% of a dataset.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 3.0 Data Analysis.
NEW QUESTION # 136
A data analyst wants to use the following tables to find all the customers who have not placed an order:
Which of the following SQL statements is the best way to accomplish this task?
Answer: B
NEW QUESTION # 137
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