The CompTIA Data+ exam will certify the successful candidate has the knowledge and skills required to transform business requirements in support of data-driven decisions through mining and manipulating data, applying basic statistical methods, and analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle.
CompTIA Data+ is an early-career data analytics certification for professionals tasked with developing and promoting data-driven business decision-making. As the importance for data analytics grows, more job roles are required to set context and better communicate vital business intelligence. Collecting, analyzing, and reporting on data can drive priorities and lead business decision-making. CompTIA Data+ validates certified professionals have the skills required to facilitate data-driven business decisions, including:
• Mining data
• Manipulating data
• Visualizing and reporting data
• Applying basic statistical methods
• Analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle
TARGET AUDIENCE:
Jobs that use CompTIA Data+
• Data Analyst
• Clinical Analyst
• Reporting Analyst
• Marketing Analyst
• Business Data Analyst
• Operations Analyst
• Business Intelligence Analyst
COURSE PREREQUISITES:
• 18–24 months of experience in a report/ business analyst job role
• Exposure to databases and analytical tools
• Basic understanding of statistics
• Data visualization experience
COURSE CONTENT:
Data Concepts and Environments – 15%
• Identify basic concepts of data schemas and dimensions
• Compare and contrast different data types
• Compare and contrast common data structures and file formatsData Mining – 25%
• Explain data acquisition concepts
• Identify common reasons for cleansing and profiling datasets
• Given a scenario, execute data manipulation techniques
• Explain common techniques for data manipulation and query optimizationData Analysis – 23%
• Given a scenario, apply the appropriate descriptive statistical methods
• Explain the purpose of inferential statistical methods
• Summarize types of analysis and key analysis techniques
• Identify common data analytics toolsVisualization – 23%
• Translate business requirements to form a report
• Use appropriate design components for reports and dashboards
• Use appropriate methods for dashboard development
• Apply the appropriate type of visualization
• Compare and contrast types of reports
Data Governance, Quality, and Controls 14%
• Summarize important data governance concepts
• Given a scenario, apply data quality control concepts
• Explain master data management (MDM) concepts
COURSE OBJECTIVE:
• Data Concepts and Environments
Boost your knowledge in identifying basic concepts of data schemas and dimensions while understanding the difference between common data structures and file formats
• Data Mining
Grow your skills to explain data acquisition concepts, reasons for cleansing and profiling datasets, executing data manipulation, and understanding techniques for data manipulation
• Visualization
Learn how to translate business requirements to form the appropriate visualization in the form of a report or dashboard with the proper design components
• Data Governance, Quality, & Controls
Increase your ability to summarize important data governance concepts and apply data quality control concepts
• Data Analysis
Gain the ability to apply the appropriate descriptive statistical methods and summarize types of analysis and critical analysis techniques
FOLLOW ON COURSES:
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