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Last Updated: Oct 16, 2026

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CompTIA DA0-001 Practice Q&A's

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CompTIA DA0-001 Exam Syllabus Topics:

TopicDetails

Data Concepts and Environments - 15%

Identify basic concepts of data schemas and dimensions.- Databases
  • Relational
  • Non-relational

- Data mart/data warehousing/data lake

  • Online transactional processing (OLTP)
  • Online analytical processing (OLAP)

- Schema concepts

  • Snowflake
  • Star

- Slowly changing dimensions

  • Keep current information
  • Keep historical and current information
Compare and contrast different data types.- Date
- Numeric
- Alphanumeric
- Currency
- Text
- Discrete vs. continuous
- Categorical/dimension
- Images
- Audio
- Video
Compare and contrast common data structures and file formats.- Structures
  • Structured
    - Defined rows/columns
    - Key value pairs
  • Unstructured
    - Undefined fields
    - Machine data

- Data file formats

  • Text/Flat file
    - Tab delimited
    - Comma delimited
  • JavaScript Object Notation (JSON)
  • Extensible Markup Language (XML)
  • Hypertext Markup Language (HTML)

Data Mining - 25%

Explain data acquisition concepts.- Integration
  • Extract, transform, load (ETL)
  • Extract, load, transform (ELT)
  • Delta load
  • Application programming interfaces (APIs)

- Data collection methods

  • Web scraping
  • Public databases
  • Application programming interface (API)/web services
  • Survey
  • Sampling
  • Observation
Identify common reasons for cleansing and profiling datasets.- Duplicate data
- Redundant data
- Missing values
- Invalid data
- Non-parametric data
- Data outliers
- Specification mismatch
- Data type validation
Given a scenario, execute data manipulation techniques.- Recoding data
  • Numeric
  • Categorical

- Derived variables
- Data merge
- Data blending
- Concatenation
- Data append
- Imputation
- Reduction/aggregation
- Transpose
- Normalize data
- Parsing/string manipulation

Explain common techniques for data manipulation and query optimization.- Data manipulation
  • Filtering
  • Sorting
  • Date functions
  • Logical functions
  • Aggregate functions
  • System functions

- Query optimization

  • Parametrization
  • Indexing
  • Temporary table in the query set
  • Subset of records
  • Execution plan

Data Analysis - 23%

Given a scenario, apply the appropriate descriptive statistical methods.- Measures of central tendency
Mean
Median
Mode
- Measures of dispersion
  • Range
    Max
    Min
  • Distribution
  • Variance
  • Standard deviation

- Frequencies/percentages
- Percent change
- Percent difference
- Confidence intervals

Explain the purpose of inferential statistical methods.- t-tests
- Z-score
- p-values
- Chi-squared
- Hypothesis testing
  • Type I error
  • Type II error

- Simple linear regression
- Correlation

Summarize types of analysis and key analysis techniques.- Process to determine type of analysis
  • Review/refine business questions
  • Determine data needs and sources to perform analysis
  • Scoping/gap analysis

- Type of analysis

  • Trend analysis
    - Comparison of data over time
  • Performance analysis
    - Tracking measurements against defined goals
    - Basic projections to achieve goals
  • Exploratory data analysis
    - Use of descriptive statistics to determine observations
  • Link analysis
    - Connection of data points or pathway
Identify common data analytics tools.- Structured Query Language (SQL)
- Python
- Microsoft Excel
- R
- Rapid mining
- IBM Cognos
- IBM SPSS Modeler
- IBM SPSS
- SAS
- Tableau
- Power BI
- Qlik
- MicroStrategy
- BusinessObjects
- Apex
- Dataroma
- Domo
- AWS QuickSight
- Stata
- Minitab

Visualization - 23%

Given a scenario, translate business requirements to form a report.- Data content
- Filtering
- Views
- Date range
- Frequency
- Audience for report
  • Distribution list
Given a scenario, use appropriate design components for reports and dashboards.- Report cover page
  • Instructions
  • Summary
    - Observations and insights

- Design elements

  • Color schemes
  • Layout
  • Font size and style
  • Key chart elements
    - Titles
    - Labels
    - Legends
  • Corporate reporting standards/style guide
    - Branding
    - Color codes
    - Logos/trademarks
    - Watermark

- Documentation elements

  • Version number
  • Reference data sources
  • Reference dates
    - Report run date
    - Data refresh date
    - Frequently asked questions (FAQs)
    - Appendix
Given a scenario, use appropriate methods for dashboard development.- Dashboard considerations
  • Data sources and attributes
    - Field definitions
    - Dimensions
    - Measures
  • Continuous/live data feed vs. static data
  • Consumer types
    - C-level executives
    - Management
    - External vendors/stakeholders
    - General public
    - Technical experts

- Development process

  • Mockup/wireframe
    - Layout/presentation
    - Flow/navigation
    - Data story planning
  • Approval granted
  • Develop dashboard
  • Deploy to production

Delivery considerations

  • Subscription
  • Scheduled delivery
  • Interactive (drill down/roll up)
    - Saved searches
    - Filtering
    - Static
    - Web interface
    - Dashboard optimization
    - Access permissions
Given a scenario, apply the appropriate type of visualization.- Line chart
- Pie chart
- Bubble chart
- Scatter plot
- Bar chart
- Histogram
- Waterfall
- Heat map
- Geographic map
- Tree map
- Stacked chart
- Infographic
- Word cloud
Compare and contrast types of reports.- Static vs. dynamic reports
  • Point-in-time
  • Real time

- Ad-hoc/one-time report
- Self-service/on demand
- Recurring reports

  • Compliance reports (e.g., financial, health, and safety)
  • Risk and regulatory reports
  • Operational reports [e.g., performance, key performance indicators (KPIs)]

- Tactical/research report

Data Governance, Quality, and Controls - 14%

Summarize important data governance concepts.- Access requirements
  • Role-based
  • User group-based
  • Data use agreements
  • Release approvals

- Security requirements

  • Data encryption
  • Data transmission
  • De-identify data/data masking

- Storage environment requirements

  • Shared drive vs. cloud based vs. local storage

- Use requirements

  • Acceptable use policy
  • Data processing
  • Data deletion
  • Data retention

- Entity relationship requirements

  • Record link restrictions
  • Data constraints
  • Cardinality

- Data classification

  • Personally identifiable information (PII)
  • Personal health information (PHI)
  • Payment card industry (PCI)

- Jurisdiction requirements

  • Impact of industry and governmental regulations

- Data breach reporting

  • Escalate to appropriate authority
Given a scenario, apply data quality control concepts.- Circumstances to check for quality
  • Data acquisition/data source
  • Data transformation/intrahops
    - Pass through
    - Conversion
  • Data manipulation
  • Final product (report/dashboard, etc.)

- Automated validation

  • Data field to data type validation
  • Number of data points

- Data quality dimensions

  • Data consistency
  • Data accuracy
  • Data completeness
  • Data integrity
  • Data attribute limitations

- Data quality rule and metrics

  • Conformity
  • Non-conformity
  • Rows passed
  • Rows failed

- Methods to validate quality

  • Cross-validation
  • Sample/spot check
  • Reasonable expectations
  • Data profiling
  • Data audits
Explain master data management (MDM) concepts.- Processes
  • Consolidation of multiple data fields
  • Standardization of data field names
  • Data dictionary

- Circumstances for MDM

  • Mergers and acquisitions
  • Compliance with policies and regulations
  • Streamline data access

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Passing Score, Duration & Questions For The CompTIA DA0-001 Exam

  • Exam Length: 90 questions
  • Time Duration: 90 minutes
  • The passing score: 675 (on scale of 100-900)
  • Languages: English
  • Format: Multiple choice and performance-based

What Do You Know About The Need For CompTIA DA0-001 Exam

CompTIA Data+ is the industry's standard for preparing for entry-level IT jobs. CompTIA Data+ validates that you have the skills needed to succeed in a technical career, and the certification can help you advance your career. CompTIA DA0-001 exam dumps will help your to make you career.

If you are interested in careers as a systems administrator, network engineer or software developer, this exam can help you show potential employers you have the necessary technical knowledge and skills.

The CompTIA Data+ certification covers topics such as storage networks, desktop support services, operating systems and more. It also includes a section on cloud computing, which helps prepare candidates for future job roles that may require them to use cloud-based technologies.

Reference: https://www.comptia.org/training/books/data-da0-001-study-guide

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Understanding CompTIA DA0-001 Exam Topics

  • Analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle

  • Applying basic statistical methods

  • Mining data

  • Visualizing and reporting data

  • Manipulating data

CompTIA Data+ Certification Sample Questions:

Question #1

Given the following athlete workout data (with inconsistent units or formats for time/distance), which of the following best describes the data quality issue?

  • A. Invalid data
  • B. Data outlier
  • C. Data inconsistency
  • D. Duplicate data
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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Question #2

A data analyst needs to present the results of an online marketing campaign to the marketing manager. The manager wants to see the most important KPIs and measure the return on marketing investment. Which of the following should the data analyst use to BEST communicate this information to the manager?

  • A. A sell-service dashboard that allows the manager to look at the company's annual budget performance
  • B. A summary with statistics, conclusions, and recommendations from the data analyst
  • C. A real-time monitor that allows the manager to view performance the day the campaign was launched
  • D. A spreadsheet of the raw data from all marketing campaigns and channels
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

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Question #3

Which of the following would be the best way to identify multicollinear attributes in a data set?

  • A. Two-sample f-test
  • B. Chi-squared test
  • C. Two-way ANOVA
  • D. Correlation coefficient
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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Question #4

An analyst is designing a dashboard to determine which site has the highest percentage of new customers. The analyst must choose an appropriate chart to include in the dashboard. The following data is available:

Which of the following types of charts should be considered to best display the data?

  • A. Include a pie chart using the site and percentage of new custorners data.
  • B. Include a line chart using the site and the percentage of new customers data.
  • C. Include a bar chart using the site and the percentage of new customers data.
  • D. Include a scatter chart using the site and the percent of new customers data.
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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Question #5

Which of the following is an example of discrete data?

  • A. The number of employees at a company
  • B. The amount of rain that falls in a storm
  • C. The power consumption in a building
  • D. The temperature at a weather station
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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