Comp TIA Data +

Training Summary
CompTIA Data+ gives you the confidence to bring data analysis to life. As the importance of 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 your organizatin’s priorities and lead business decision-making. CompTIA Data+ validates you have the skills required to facilitate data-driven business decisions. Data+ is an ideal certification for not only data-specific careers, but other career paths that can benefit, such as marketing specialists, financial analysts, human resource analysts, or clinical health care analysts.
Attendees should meet the following prerequisites:
  • 18–24 months of hands-on experience working in a business intelligence, report/data analyst job role.
  • Exposure to databases and analytics tools.
  • Basic understanding of statistics.
  • Data visualization experience.
5 Days/Lecture & Lab
This course is designed for:
  • Data Analyst
  • Business Intelligence Analyst
  • Reporting Analyst
  • Marketing Analyst
  • Clinical Analyst
  • Business Data Analyst
  • Operations Analyst
Course Topics
  • Identifying Basic Concepts of Data Schemas
  • Understanding Different Data Systems
  • Understanding Types and Characteristics of Data
  • Comparing and Contrasting Different Data Structures, Formats, and Markup Languages
  • Explaining Data Integration and Collection Methods
  • Identifying Common Reasons for Cleansing and Profiling Data
  • Executing Different Data Manipulation Techniques
  • Explaining Common Techniques for Data Manipulation and Optimization
  • Applying Descriptive Statistical Methods
  • Describing Key Analysis Techniques
  • Understanding the Use of Different Statistical Methods
  • Using the Appropriate Type of Visualization
  • Expressing Business Requirements in a Report Format
  • Designing Components for Reports and Dashboards
  • Distinguishing Different Report Types
  • Summarizing the Importance of Data Governance
  • Applying Quality Control to Data
  • Explaining Master Data Management Concepts
  • Appendix: Identifying Common Data Analytics Tools

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