CompTIA DA0-002 Deutsch - DA0-002 Zertifikatsfragen

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CompTIA DA0-002 Prüfungsplan:

ThemaEinzelheiten
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
  • Data Concepts and Environments: This section of the exam measures the skills of a Junior Data Analyst and focuses on understanding core data concepts such as database types, schema structures, and data formats. It highlights differences between structured and unstructured data, compares file types like CSV, JSON, and XML, and introduces key ideas about data dimensions and slowly changing dimensions. Knowing how data is stored and organized helps professionals better prepare for analysis and reporting tasks.
Thema 3
  • Data Analysis: This section of the exam measures skills of a Reporting Analyst and includes foundational knowledge of statistical methods such as averages, variances, and standard deviation. It covers how to use data to find patterns, track performance, and make predictions. This domain also introduces hypothesis testing, regression, correlation, and different types of analysis like exploratory and trend analysis. Candidates should also be aware of common tools used for analysis, including Excel, SQL, Python, R, and popular BI platforms like Tableau and Power BI.
Thema 4
  • 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 5
  • This section of the exam measures skills of a Data Governance Associate and introduces principles for keeping data secure, accurate, and compliant. It covers access controls, encryption, classification of sensitive data like PII and PHI, and legal requirements tied to data use. Candidates must know how to apply quality checks, validate data, and manage master data effectively. It also addresses best practices for maintaining integrity through data dictionaries, audits, and standardisation processes.

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CompTIA Data+ Exam DA0-002 Prüfungsfragen mit Lösungen (Q109-Q114):

109. Frage
A business intelligence analyst is creating an employee retention dashboard that looks at data from the last five years. The analyst is interested in identifying patterns that can be studied further. Which of the following is the best method to apply to the dashboard?

Antwort: A

Begründung:
Descriptive analytics summarizes historical data to identify trends, patterns, and relationships.
Since the analyst is examining employee retention data from the last five years to discover patterns for further study, descriptive analytics is the most appropriate method.


110. Frage
A company wants to limit an employee's access to a production environment. Which of the following access control practices is the best to implement?

Antwort: C

Begründung:
This question falls under theData Governancedomain, focusing on access control practices for data security.
The task is to limit an employee's access to a production environment, requiring a structured approach.
* Mandatory (Option A): Mandatory access control (MAC) uses strict, system-enforced rules (e.g., military settings), but it's overly rigid for most companies.
* Time-based (Option B): Time-based access limits access to specific times, which doesn't address general production environment access.
* Attribute-based (Option C): Attribute-based access control (ABAC) uses attributes (e.g., department, location), but it's complex and not the simplest solution.
* Role-based (Option D): Role-based access control (RBAC) assigns permissions based on the employee's role, ensuring they only access what's needed for their job, making it the best practice for limiting production access.
The DA0-002 Data Governance domain includes "data privacy concepts," and role-based access control is a widely adopted practice for limiting access in production environments.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.


111. Frage
A data analyst is creating a pivot table for a large data set for an upcoming board meeting. Which of the following is the purpose of the pivot table?

Antwort: C

Begründung:
A pivot table is used to aggregate, summarize, and analyze large data sets, enabling quick insights such as totals, averages, and groupings.


112. Frage
Which of the following data repositories stores unaltered data?

Antwort: B

Begründung:
A data lake stores raw, unaltered data in its native format, including structured, semi-structured, and unstructured data. This allows organizations to retain data as originally collected and transform it later when needed for analysis.


113. Frage
Given the following tables:

Which of the following data privacy practices is being used to protect employees' email addresses when creating a report?

Antwort: C

Begründung:
Masking hides sensitive data by replacing portions of the original value with obscured characters, such as replacing email addresses with "xxxxx@company.com" while preserving the format.


114. Frage
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