DA0-002 Zertifizierungsfragen, CompTIA DA0-002 PrüfungFragen

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CompTIA DA0-002 Prüfungsplan:

Thema	Einzelheiten
Thema 1	Data Mining: This section of the exam measures skills of a Business Intelligence Analyst and covers how data is collected, cleaned, and prepared for analysis. It explains methods like ETL and ELT for data integration, as well as web scraping, API use, and survey data collection. Candidates are expected to identify issues like missing or duplicated data and apply techniques like filtering, sorting, merging, and normalizing. The section also touches on query optimization strategies to improve data handling efficiency.
Thema 2	Visualization: This section of the exam measures skills of a Data Visualisation Specialist and focuses on turning raw data into clear, visual insights. It teaches how to match visual formats like bar charts, heat maps, and line graphs to specific audiences and needs. Candidates must understand how to create dashboards and reports using proper design elements such as labels, layout, branding, and colour schemes. This section also includes best practices for dashboard development and delivery through various platforms and user access levels.
Thema 3	5.0 Data Governance, Quality, and Controls

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DA0-002 Exam Fragen - DA0-002 Examengine

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CompTIA Data+ Exam DA0-002 Prüfungsfragen mit Lösungen (Q49-Q54):

49. Frage
A data analyst is reviewing a new data source that contains employee IDs, job titles, dates of birth, addresses, years of service, and employees' birth months. Which of the following inconsistencies should the analyst identify?

A. Redundancy
B. Completeness
C. Duplication
D. Outliers

Antwort: A

Begründung:
Redundancy occurs when the same information can be derived from other data already present in the dataset. Since the data source contains both dates of birth and employees' birth months, the birth month is redundant because it can be extracted directly from the date of birth.

50. Frage
A data analyst calculated the average score per student without making any changes to the following table:

Which of the following exploration techniques should the analyst have considered before calculating the average?

A. Redundancy
B. Binning
C. Grouping
D. Duplication

Antwort: D

Begründung:
Duplicate records in the dataset would skew the average score calculation, so identifying and handling duplication should be done before performing the analysis.

51. Frage
A data analyst needs to remove all duplicate values between two tables, "Employees" and "Managers," using SQL SELECT statements. Which of the following should the analyst use for this task?

A. SELECT * FROM Employees CROSS JOIN SELECT * FROM Managers
B. SELECT * FROM Employees UNION SELECT * FROM Managers
C. SELECT * FROM Employees UNION ALL SELECT * FROM Managers
D. SELECT * FROM Employees JOIN SELECT * FROM Managers

Antwort: B

Begründung:
This question pertains to theData Acquisition and Preparationdomain, focusing on combining and deduplicating data using SQL. The task is to remove duplicates between two tables, meaning the analyst needs a unique set of records from both.
* SELECT * FROM Employees UNION ALL SELECT * FROM Managers (Option A): UNION ALL combines all rows from both tables, including duplicates, which doesn't meet the requirement.
* SELECT * FROM Employees UNION SELECT * FROM Managers (Option B): UNION combines rows from both tables and automatically removes duplicates, providing a unique set of records, which fits the task.
* SELECT * FROM Employees JOIN SELECT * FROM Managers (Option C): This syntax is incorrect; a JOIN requires an ON clause, and it wouldn't remove duplicates.
* SELECT * FROM Employees CROSS JOIN SELECT * FROM Managers (Option D): A CROSS JOIN creates a Cartesian product, resulting in all possible combinations, not removing duplicates.
The DA0-002 Data Acquisition and Preparation domain includes "executing data manipulation," and UNION is the correct SQL operation for combining tables while removing duplicates.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 2.0 Data Acquisition and Preparation.

52. Frage
A Chief Executive Officer requests a report that must:
- Summarize the company metrics in a simple way.
- Be clear and concise.
- Be easily understood by all company levels.
- Be accessible and updated without manual intervention.
Which of the following communication approaches best meets these requirements?

A. Open data portal
B. Slide presentation
C. Key performance indicator dashboard
D. Executive summary

Antwort: C

Begründung:
A key performance indicator dashboard provides a clear, concise, and easily understandable view of important business metrics. It can be updated automatically from data sources, allowing executives and employees at all levels to access current information without manual intervention.

53. Frage
An analyst needs to produce a final dataset using the following tables:
CourseID
SectionNumber
StudentID
MATH1000
1
10009
MATH1000
2
10007
PSYC1500
1
10009
PSYC1500
1
10015
StudentID
FirstName
LastName
10009
Jane
Smith
10007
John
Doe
10015
Robert
Roe
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?

A. Join
B. Aggregate
C. Group
D. Filter

Antwort: A

Begründung:
This question falls under theData Acquisition and Preparationdomain, focusing on combining tables to produce a dataset. The task requires combining the Courses and Students tables to include student names with course details, based on the StudentID.
* Aggregate (Option A): Aggregation (e.g., SUM, COUNT) summarizes data, not suitable for combining tables to include names.
* Join (Option B): A join operation (e.g., INNER JOIN on StudentID) combines the tables, matching records to produce the requested output with CourseID, SectionNumber, StudentID, FirstName, and LastName.
* Group (Option C): Grouping is used for aggregation (e.g., GROUP BY in SQL), not for combining tables.
* Filter (Option D): Filtering selects specific rows, not relevant for combining tables.
The DA0-002 Data Acquisition and Preparation domain includes "executing data manipulation," such as joining tables to create a unified dataset.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 2.0 Data Acquisition and Preparation.

54. Frage
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