CompTIA Data+

About Course

CompTIA Data+ is an early-career data analytics certification for professionals tasked with developing and promoting data-driven business decision-making. Data+ is an ideal certification for not only data-specific careers, but other career paths can benefit from analytics processes and data analytics knowledge. Jobs like marketing specialists, financial analysts, human resource analysts or clinical health care analysts can optimise performance and make well-informed decisions when they use and evaluate data correctly.

CompTIA Data+ gives your team members the confidence to bring data analysis to life. As the importance for data analytics grows, more job roles are required to set context and better communicate vital business intelligence. Collecting, analysing, and reporting on data can drive your organisation’s priorities and lead business decision-making.

Top Data+ Job Titles

• Data Analyst.

• Business Intelligence Analyst.

• Reporting Analyst.

• Marketing Analyst.

• Clinical Analyst.

• Business Data Analyst.

• Operations Analyst.

Course Content

Data Concepts and Environments 15%
• Identify basic concepts of data schemas and dimensions • Compare and contrast different data types • Understand the difference between common data structures and file format

Data Mining 25%
Explain data acquisition concepts • Identify common reasons for cleansing and profiling datasets • Ability to execute data manipulation techniques • Explain common techniques for data manipulation and query optimization

Data Analysis 23%
• Ability to 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 tools

Visualization 23%
• Ability to translate business requirements to form a report • Use appropriate design components for reports and dashboards • Use appropriate methods for dashboard development • Ability to apply the appropriate type of visualization • Compare and contrast types of reports

Data Governance, Quality, & Controls 14%
• Summarize important data governance concepts • Apply data quality control concepts • Explain master data management (MDM) concepts

Student Ratings & Reviews

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About Course

What Will You Learn?

Course Content

Data Concepts and Environments 15%
• Identify basic concepts of data schemas and dimensions • Compare and contrast different data types • Understand the difference between common data structures and file format

Data Mining 25%
Explain data acquisition concepts • Identify common reasons for cleansing and profiling datasets • Ability to execute data manipulation techniques • Explain common techniques for data manipulation and query optimization

Data Analysis 23%
• Ability to 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 tools

Data Governance, Quality, & Controls 14%
• Summarize important data governance concepts • Apply data quality control concepts • Explain master data management (MDM) concepts

Resources

About Course

What Will You Learn?

Course Content

Data Concepts and Environments 15% • Identify basic concepts of data schemas and dimensions • Compare and contrast different data types • Understand the difference between common data structures and file format

Data Mining 25% Explain data acquisition concepts • Identify common reasons for cleansing and profiling datasets • Ability to execute data manipulation techniques • Explain common techniques for data manipulation and query optimization

Data Analysis 23% • Ability to 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 tools

Data Governance, Quality, & Controls 14% • Summarize important data governance concepts • Apply data quality control concepts • Explain master data management (MDM) concepts

Student Ratings & Reviews

Resources

Data Concepts and Environments 15%
• Identify basic concepts of data schemas and dimensions • Compare and contrast different data types • Understand the difference between common data structures and file format

Data Mining 25%
Explain data acquisition concepts • Identify common reasons for cleansing and profiling datasets • Ability to execute data manipulation techniques • Explain common techniques for data manipulation and query optimization

Data Analysis 23%
• Ability to 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 tools

Data Governance, Quality, & Controls 14%
• Summarize important data governance concepts • Apply data quality control concepts • Explain master data management (MDM) concepts