CompTIA Data+ (DA0-002) Cert Prep

Course details

In this comprehensive course, expert Mike Chapple helps you prepare for the CompTIA Data+ DA0-002 certification. Mike walks you through the essential skills needed to analyze, prepare, and visualize data, ensuring you’re ready to tackle real-world business challenges. Discover how to transform raw data into actionable insights, create impactful visualizations, and adhere to data governance and compliance standards. Along the way, Mike covers key concepts such as statistical analysis, data quality assurance, and visualization techniques, helping you master the skills needed for certification success. By the end of the course, you’ll be well-equipped to confidently pass the Data+ exam and excel in data-driven roles.

Learning objectives
Prepare for the CompTIA Data+ exam.
Translate business requirements in support of data-driven decisions by acquiring, preparing, and transforming data.
Use industry-standard tools and emerging technologies to create appropriate reports and visualizations.
Apply basic statistical methods and analyze complex data sets while adhering to governance and quality standards throughout the entire data life cycle.

Concepts

Introduction

About the data+ exam

The Data+ Exam

The Data+ exam
Careers in analytics
The value of certification
Study resources

Inside the Data+ Exam

In-person exam environment
At-home testing
Data+ question types
Passing the Data+ exam
Exam tips

Domain 1 - Data Concepts and Environments

Overview of the data concepts and environments domain

Understanding Data

The value of data
Structured vs unstructured data
Tabular data
Key-value pairs

Data Types

Numeric data
Boolean data
String data
Discrete vs. continuous data
Dates and times
Multimedia data
Spatial data
Unique identifiers

Data File Formats

Text files
JSON data
HTML data
XML data
Binary data

Data Storage

Relational databases
OLTP and OLAP
Non-relational databases
Data schemas

Data Sources

Public databases
Application programming interfaces (APIs)
Web scraping
Files and logs

Cloud Computing

What is the cloud
Drivers for cloud computing
Cloud providers
Cloud deployment models
Virtualization
Containerization
Cloud storage options

Data Analysis Tools

Data analysis tools
Microsoft excel
Programming languages
Coding environments
Statistics packages
Business intelligence software
SQL and database tools

Artificial Intelligence

AI and analytics
Generative AI
Robotic process automation

Domain 2 - Data Acquisition and Preparation

Overview of the data acquisition and preparation domain

Data Acquisition and Integration

ETL and ELT processes
Surveys and observation
Sampling

SQL Queries

Structured query language
SELECT statement
Sorting results
Filtering data
NULL values
Aggregating data
Grouping data
String manipulation
Working with dates
Derived values
Set operations
Join operations
Inner joins
Joining multiple tables
Outer joins
Nested queries

Query Optimization

Indexing
Record subsets
Query execution plans
Parameterization

Identifying Data Inconsistencies

Duplicate and redundant data
Missing data and completeness
Invalid data and outliers
Handling outliers

Data Transformation and Cleansing

Combining datasets
Conversion, standardization, and scaling
Regular expressions
Binning and clustering
Data augmentation
Exploding data

Domain 3 - Data Analysis

Overview of the data analysis domain

Communicating Data Analyses

Communicating to your audience
Design considerations

Statistics

Statistical methods
Mean, median, and mode
Range and distribution
Variance and standard deviation
Function types

Troubleshooting Analysis

Common issues
Troubleshooting techniques

Domain 4 - Visualization and Reporting

Overview of the visualization and reporting domain

Visual Elements of Reporting

Reporting requirements
Cover pages
Design elements
Documentation elements

Visualization Types

Line chart
Scatterplots and bubble charts
Pie charts
Bar charts and histograms
Waterfall charts
Heat maps and geographic maps
Tree maps
Word clouds and infographics
Pivot tables

Reports and Dashboards

Reports
Dashboards
Dashboard design
Dashboard development
Dashboard delivery

Troubleshooting Reports

Reporting Issues
Report validation

Domain 5 - Data Governance

Overview of the data governance domain

Data Governance Programs

What is data stewardship
Exploring data stewardship roles
Qualities of a good data steward
Data stewardship responsibilities

Database Documentation

Data dictionaries
Data flow documentation
Hierarchy structure
Transparency and trust
Data versioning
Metadata

Regulatory Compliance

Today's regulatory landscape
Health insurance portability and accountability act (HIPAA)
Family educational rights and privacy act (FERPA)
Gramm leach bliley act (GLBA)
Data breach notification laws
International data transfers

Preserving Individual Privacy

Privacy program development
Generally accepted privacy principles
Data anonymization
Data obfuscation
Data sharing and transfers
Data ethics

Protecting Data Security

Goals of information security
Preserving data confidentiality
Building an access management program
Authentication, authorization, and accounting
Managing the data lifecycle
Data classification
Control and risk frameworks
Audits and assessments

Maintaining Data Quality

Implementing master data management
Developing data definitions
Protecting data quality
Validating data quality
Testing
Source control

What's Next

Preparing for the exam