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CompTIA Data+ (CompTIA Data+Certification)

CompTIA
5 Days
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Course Summary
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Description

CompTIA Data+ is an early-career data analytics certification for professionals tasked with developing and promoting data-driven business decision-making.

CompTIA Data+ gives you 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, 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

Objectives

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+ 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, analyzing, and reporting on data can drive your organization’s priorities and lead business decision-making.
CompTIA Data+ validates your team members 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

 

What Skills Will You Learn?

HARDWARE

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

WINDOWS OPERATING SYSTEMS

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

SOFTWARE TROUBLESHOOTING

Data Analysis

Gain the ability to apply the appropriate descriptive statistical methods and summarize types of analysis and critical analysis techniques

NETWORKING

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

NETWORKING

Data Governance, Quality, & Controls

Increase your ability to summarize important data governance concepts and apply data quality control concepts

Prerequisites

CompTIA recommends 18–24 months of experience in a report/business analyst job role, exposure to databases and analytical tools, a basic understanding of statistics, and data visualization experience

Outline

Lesson 1: Identifying Basic Concepts of Data Schemas

Lesson 2: Understanding Different Data Systems

Lesson 3: Understanding Types and Characteristics of Data

Lesson 4: Comparing and Contrasting Different Data Structures, Formats, and Markup Languages

Lesson 5: Explaining Data Integration and Collection Methods

Lesson 6: Identifying Common Reasons for Cleansing and Profiling Data

Lesson 7: Executing Different Data Manipulation Techniques

Lesson 8: Explaining Common Techniques for Data Manipulation and Optimization

Lesson 9: Applying Descriptive Statistical Methods

Lesson 10: Describing Key Analysis Techniques

Lesson 11: Understanding the Use of Different Statistical Methods

Lesson 12: Using the Appropriate Type of Visualization

Lesson 13: Expressing Business Requirements in a Report Format

Lesson 14: Designing Components for Reports and Dashboards

Lesson 15: Distinguishing Different Report Types

Lesson 16: Summarizing the Importance of Data Governance

Lesson 17: Applying Quality Control to Data

Lesson 18: Explaining Master Data Management Concepts

Appendix A: Identifying Common Data Analytics Tools