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CompTIA DA0-002 Exam Syllabus Topics:

SectionWeightObjectives
Data Mining25%- Data acquisition and collection
  • 1. Data sources and ingestion methods
  • 2. APIs and connectors
  • 3. ETL/ELT processes
- Data preparation and cleansing
  • 1. Data normalization and transformation
  • 2. Data cleaning techniques
  • 3. Handling missing values and duplicates
- Data enrichment and integration
  • 1. Data mapping and lineage
  • 2. Joining and merging datasets
  • 3. Derived columns and calculated fields
Data Analysis24%- Analysis tools and techniques
  • 1. Libraries and functions for analysis
  • 2. SQL for data analysis
  • 3. BI platforms and notebooks
- Descriptive statistics
  • 1. Data distributions
  • 2. Measures of central tendency
  • 3. Measures of dispersion
- Inferential statistics
  • 1. Confidence intervals
  • 2. Hypothesis testing
  • 3. Correlation and regression basics
Visualization15%- Storytelling with data
  • 1. Executive summaries and key insights
  • 2. Narrative techniques for data communication
  • 3. Audience-appropriate visuals
- Dashboard and report design
  • 1. Chart types and their applications
  • 2. Dashboard components and layout
  • 3. Visualization best practices
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
Data Governance, Quality, and Controls16%- Data governance frameworks
  • 1. Policies, standards, and procedures
  • 2. Compliance requirements (GDPR, CCPA, etc.)
  • 3. Data stewardship and ownership
- Security and privacy
  • 1. Foundational AI considerations in data lifecycle
  • 2. Access controls and encryption
  • 3. Data classification and protection
  • 4. Audit trails and logging
- Data quality management
  • 1. Quality assessment and monitoring
  • 2. Remediation strategies
  • 3. Quality dimensions (accuracy, completeness, consistency)

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CompTIA Data+ Exam Sample Questions (Q90-Q95):

NEW QUESTION # 90
Given the following table:
ID
Value
1
1.5
2
24.456
3
113
Which of the following data types should an analyst use for the numeric values in the Value column?

Answer: C

Explanation:
This question falls under theData Concepts and Environmentsdomain of CompTIA Data+ DA0-002, focusing on selecting appropriate data types for a given dataset. The Value column contains decimal numbers (1.5, 24.456, 113), requiring a data type that supports such values.
* Double (Option A): Double is a floating-point data type that supports decimals with higher precision than Float, but it's often overkill for typical datasets unless very high precision is needed, which isn't indicated here.
* Float (Option B): Float is a floating-point data type that supports decimal numbers (e.g., 1.5, 24.456) and is commonly used for such values in databases, making it the best choice.
* Boolean (Option C): Boolean is for true/false values, not numeric data.
* Integer (Option D): Integer is for whole numbers, but the values (e.g., 1.5, 24.456) have decimals, so Integer is not suitable.
The DA0-002 Data Concepts and Environments domain includes understanding "data schemas and dimensions," such as selecting data types like Float for decimal numeric values.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 1.0 Data Concepts and Environments.


NEW QUESTION # 91
A data analyst is creating a report about cars sold within the last twelve months. The current data set only contains information from the last ten months. Which of the following is the most appropriate way to accomplish this task?

Answer: A

Explanation:
Extracting the missing records from the previous year and appending them ensures the dataset includes the full twelve-month period required for accurate reporting.


NEW QUESTION # 92
A senior manager needs a report that can be generated and accessed at any time. Which of the following delivery methods should a data analyst use?

Answer: B


NEW QUESTION # 93
Which of the following best describes the function of a data type?

Answer: C


NEW QUESTION # 94
A data analyst troubleshoots a dashboard every day for a week. Which of the following techniques best addresses how to validate the data moving forward?

Answer: A

Explanation:
This question pertains to theData Governancedomain, focusing on ensuring data quality and reliability in dashboards over time. Daily troubleshooting indicates a recurring issue, and the task is to validate data moving forward.
* Inquiring about structure changes (Option A): This might identify past issues but doesn't provide ongoing validation.
* Setting up monitoring alerts (Option B): Monitoring alerts can automatically notify the analyst of data issues (e.g., missing updates, errors), providing a proactive way to validate data continuously.
* Reaching out to users daily (Option C): This is inefficient and reactive, not a sustainable validation method.
* Rebuilding the dashboard (Option D): Rebuilding might fix current issues but doesn't ensure future validation.
The DA0-002 Data Governance domain includes "data quality control concepts," such as implementing monitoring to ensure data reliability in dashboards.
Reference: CompTIA Data+ DA0-002 Draft Exam Objectives, Domain 5.0 Data Governance.


NEW QUESTION # 95
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