CompTIA DA0-002 Questions Exam Reliable IT Certifications | DA0-002: CompTIA Data+ Exam

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CompTIA DA0-002 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Visualization15%- Dashboard and report design
  • 1. Dashboard components and layout
  • 2. Chart types and their applications
  • 3. Visualization best practices
- Storytelling with data
  • 1. Audience-appropriate visuals
  • 2. Executive summaries and key insights
  • 3. Narrative techniques for data communication
Topic 2: Data Concepts and Environments20%- Data structures and formats
  • 1. Common data formats (JSON, XML, CSV)
  • 2. Structured, semi-structured, and unstructured data
  • 3. File types and their use cases
- Data types and metadata
  • 1. Data types (string, numeric, Boolean, date)
  • 2. Metadata and its role in data management
- Database fundamentals
  • 1. Schemas and data models
  • 2. Cloud and containerized data environments
  • 3. Relational vs. non-relational databases
Topic 3: Data Analysis24%- Analysis tools and techniques
  • 1. BI platforms and notebooks
  • 2. Libraries and functions for analysis
  • 3. SQL for data analysis
- Inferential statistics
  • 1. Hypothesis testing
  • 2. Confidence intervals
  • 3. Correlation and regression basics
- Descriptive statistics
  • 1. Data distributions
  • 2. Measures of central tendency
  • 3. Measures of dispersion
Topic 4: Data Governance, Quality, and Controls16%- Data quality management
  • 1. Quality dimensions (accuracy, completeness, consistency)
  • 2. Quality assessment and monitoring
  • 3. Remediation strategies
- Security and privacy
  • 1. Data classification and protection
  • 2. Audit trails and logging
  • 3. Access controls and encryption
  • 4. Foundational AI considerations in data lifecycle
- Data governance frameworks
  • 1. Data stewardship and ownership
  • 2. Compliance requirements (GDPR, CCPA, etc.)
  • 3. Policies, standards, and procedures
Topic 5: Data Mining25%- Data enrichment and integration
  • 1. Data mapping and lineage
  • 2. Derived columns and calculated fields
  • 3. Joining and merging datasets
- Data preparation and cleansing
  • 1. Data cleaning techniques
  • 2. Data normalization and transformation
  • 3. Handling missing values and duplicates
- Data acquisition and collection
  • 1. ETL/ELT processes
  • 2. Data sources and ingestion methods
  • 3. APIs and connectors

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CompTIA Data+ Exam Sample Questions (Q95-Q100):

NEW QUESTION # 95
A data analyst is compiling a report called "Product Category Sales Performance Summary Report" based on the following table:

Which of the following charts is the most appropriate?

Answer: C

Explanation:
A column chart is the most appropriate choice for a Product Category Sales Performance Summary Report because it effectively compares sales performance across discrete categories such as Baby, Home, Garden, and Furniture. It allows stakeholders to easily identify which product categories generate higher or lower sales and makes category-to-category comparisons clear.


NEW QUESTION # 96
A product goes viral on social media, creating high demand. Distribution channels are facing supply chain issues because the testing and training models that are used for sales forecasting have not encountered similar demand. Which of the following best describes this situation?

Answer: C

Explanation:
Data drift occurs when real-world data patterns change from what the model was trained on, such as an unexpected surge in demand that the model has not previously encountered, leading to inaccurate predictions.


NEW QUESTION # 97
A company has a document that includes the names of key metrics and the standard for how those metrics are calculated company-wide. Which of the following describes this documentation?

Answer: B

Explanation:
This question falls under theData Concepts and Environmentsdomain, which involves understanding documentation types related to data management. The document describes key metrics and their calculation standards, which points to a specific type of metadata documentation.
* Data dictionary (Option A): A data dictionary defines data elements, including metrics, their meanings, and calculation methods, ensuring consistency across the organization. This matches the description.
* Data explainability report (Option B): This term is more associated with AI/ML, explaining model decisions, not metric definitions.
* Data lineage (Option C): Data lineage tracks the flow of data through systems, not metric definitions or calculations.
* Data flow diagram (Option D): A data flow diagram visualizes data processes, not metric standards.
The DA0-002 Data Concepts and Environments domain includes understanding "basic concepts of data schemas and dimensions" , and a data dictionary is a foundational tool for defining metrics.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments


NEW QUESTION # 98
Which of the following is the best tool for creating a dynamic dashboard?

Answer: A


NEW QUESTION # 99
A data analyst is working on an initial analysis of the dataset in the following table:

Which of the following issues should the analyst flag in the data report?

Answer: B

Explanation:
The value 245 is significantly higher than the other counts, indicating an outlier that should be flagged for further investigation.


NEW QUESTION # 100
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