CompTIA Data+Certification Exam
Objectives
EXAM NUMBER: DA0-001

About the Exam
Candidates are encouraged to use this document to help prepare for the CompTIA Data+ (DA0001) certification exam. This exam will certify the successful candidate has the knowledge andskills required to transform business requirements in support of data-driven decisions by:• Mining data
• Manipulating data
• Applying basic statistical methods• Analyzing complex datasets while adhering to governance and quality
standards throughout the entire data life cycle
This is equivalent to 18–24 months of hands-on experience working in a business intelligencereport/data analyst job role. These content examples are meant to clarify the test objectives andshould not be construed as a comprehensive listing of all the content of this examination.
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PLEASE NOTE
The lists of examples provided in bulleted format are not exhaustive lists. Other examples oftechnologies, processes, or tasks pertaining to each objective may also be included on the exam
although not listed or covered in this objectives document. CompTIA is constantly reviewing thecontent of our exams and updating test questions to be sure our exams are current and the securityof the questions is protected. When necessary, we will publish updated exams based on testing
exam objectives. Please know that all related exam preparation materials will still be valid.

CompTIA Data+ Certification Exam Objectives 2.0 (Exam Number: DA0-001)

TEST DETAILS
Required examDA0-001

Number of questions

90

Types of questions

Multiple choice and performance-based

Length of test

90 minutes

Recommended experience • 18–24 months of experience in a report/businessanalyst job role
• Exposure to databases and analytical tools• Basic understanding of statistics• Data visualization experience
Passing score

675 (on scale of 100–900)

EXAM OBJECTIVES (DOMAINS)
The table below lists the domains measured by this examinationand the extent to which they are represented:
DOMAINPERCENTAGE OF EXAMINATION

1.0 Data Concepts and Environments

15%

2.0 Data Mining

25%

3.0 Data Analysis

23%

4.0 Visualization

23%

5.0 Data Governance, Quality, and Controls
Total

14%
100%

CompTIA Data+ Certification Exam Objectives 2.0 (Exam Number: DA0-001)

1.0 Data Concepts and Environments
1.1Identify 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- Star1.2

Compare and contrast different data types.
• Date• Numeric• Alphanumeric• Currency• Text1.3• Slowly changing dimensions- Keep current information- Keep historical andcurrent information• Discrete vs. continuous• Categorical/dimension• Images• Audio• VideoCompare 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)CompTIA Data+ Certification Exam Objectives 2.0 (Exam Number: DA0-001)

2.0 Data Mining
2.1

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

2.2• 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

2.4- Survey- Sampling- Observation

Identify common reasons for cleansing and profiling datasets.
• Duplicate data
• Redundant data
• Missing values• Invalid data

2.3

• Data collection methods- Web scraping- Public databases- Application programming
interface (API)/web services• Data blending• Concatenation• Data append• Imputation• Reduction/aggregation

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

CompTIA Data+ Certification Exam Objectives 2.0 (Exam Number: DA0-001)• Transpose• Normalize data
• Parsing/string manipulation

3.0 Data Analysis
3.1

Given a scenario, apply the appropriate descriptive statistical methods.
• Measures of central tendency- Mean- Median- Mode3.2• 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 andsources to perform analysis- Scoping/gap analysis• Type of analysis- Trend analysis		 - Comparison of data over time

3.4

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

Explain the purpose of inferential statistical methods.
• t-tests• Z-score• p-values• Chi-squared

3.3• Measures of dispersion- Range		- Max		- Min- Distribution- Variance- Standard deviation- 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.
(The intent of this objective is NOT to test specific vendor feature sets nor the purposes of the 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

CompTIA Data+ Certification Exam Objectives 2.0 (Exam Number: DA0-001)• Apex• Dataroma• Domo• AWS QuickSight• Stata• Minitab

4.0 Visualization
4.1

Given a scenario, translate business requirements to form a report.
• Data content• Filtering• Views• Date range

4.2

Given a scenario, use appropriate designcomponents 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

4.3• Frequency• Audience for report- Distribution list

- 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

CompTIA Data+ Certification Exam Objectives 2.0 (Exam Number: DA0-001)- Static- Web interface- Dashboard optimization- Access permissions

4.0 Visualization
4.4

Given a scenario, apply the appropriate type of visualization.
• Line chart• Pie chart• Bubble chart• Scatter plot
• Bar chart• Histogram• Waterfall

4.5• Heat map• Geographic map• Tree map• Stacked chart• Infographic• Word cloudCompare 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 performanceindicators (KPIs)]• Tactical/research report

CompTIA Data+ Certification Exam Objectives 2.0 (Exam Number: DA0-001)

5.0 Data Governance, Quality, and Controls
5.1

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

5.2- Personal health information (PHI)- Payment card industry (PCI)• Jurisdiction requirements- Impact of industry andgovernmental 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

5.3• Use requirements- Acceptable use policy- Data processing- Data deletion- Data retention• Entity relationship requirements- Record link restrictions- Data constraints- Cardinality• Data classification- Personally identifiableinformation (PII)• 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

CompTIA Data+ Certification Exam Objectives 2.0 (Exam Number: DA0-001)

CompTIA Data+ (DA0-001) Acronym List
The following is a list of acronyms that appear on the CompTIA
Data+ exam. Candidates are encouraged to review the complete
list and attain a working knowledge of all listed acronyms as apart of a comprehensive exam preparation program.
ACRONYMDEFINITIONAPIAWSBIELTETL
FAQs
GDPRHTMLJSON
KPIMDMOLAPOLTP
P&L
PCIPHIPIIRDBMSSDLCSQLXML

Application Programming Interface
Amazon Web Services
Business Intelligence
Extract, Load, Transform
Extract, Transform, Load
Frequently Asked Questions
General Data Protection Regulation
Hypertext Markup Language
JavaScript Object Notation
Key Performance Indicator
Master Data Management
Online Analytical Processing
Online Transaction Processing
Profit and Loss
Payment Card Industry
Personal Health Information
Personally Identifiable Information
Relational Database Management System
Software Development Life Cycle
Structured Query Language
Extensible Markup Language

CompTIA Data+ Certification Exam Objectives 2.0 (Exam Number: DA0-001)

CompTIA Data+ Proposed Hardware and Software List
CompTIA has included this sample list of hardware and software to assist
candidates as they prepare for the Data+ exam. This list may also be helpful
for training companies that wish to create a lab component for their training
offering. The bulleted lists below each topic are samples and are not exhaustive.
HARDWARE

SOFTWARE• Desktop/laptop- High processing power forlarge volume analyses- Lower processing power forsmaller volume analyses• Internet access• Cloud environment• SQL environment to run scripts(SQL Lite, Management Studio, etc.)• Eclipse• Anaconda• R Studio• Database modeling tool
• Microsoft Office Suite• Visualization tools (Tableau, Power BI, etc.)• Reporting tools• Sample datasets (Kaggle)© 2020 CompTIA, Inc., used under license by CompTIA, Inc. All rights reserved. All certification programs and education related to such programs are operated
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herein may be trademarks or service marks of CompTIA, Inc. or of their respective owners. Reproduction or dissemination prohibited without the written consentof CompTIA, Inc. Printed in the U.S. 07390-Jan2020