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CompTIA Data+ (DA0-001)
Class
Javier Irizarry Riveiro
The CompTIA Data+ course is specifically designed to provide participants with a solid foundation in data analytics, emphasizing the practical application of data analysis to support organizational decision-making. This course covers the fundamentals of data concepts, statistical methods, data processing, and the use of analytics tools. It prepares students to effectively interpret and present data, crucial for roles in data analysis, business analysis, and data-driven decision-making. Upon completion of this course, students will be prepared to sit for the CompTIA Data+ certification exam, which validates competency in data analytics as a pathway to a career in data science.
/files/799524/CompTIA_Data_DA0-001_Syllabus.pdf
GENERAL OBJECTIVES
This course will enable students to:
- Understand basic concepts of data analytics and data science.
- Learn to process data sets, ensuring data quality and accuracy.
- Utilize statistical methods to analyze collected data.
- Gain proficiency in data visualization techniques to effectively communicate data insights.
- Explore data analytics tools and software to support data-driven decisions.
- Develop skills to interpret and present complex data to stakeholders.
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 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
Here is the class outline:
1. Lesson 1: Identifying Basic Concepts of Data Schemas |
2. Lesson 2: Understanding Different Data Systems |
3. Lesson 3: Understanding Types and Characteristics of Data |
4. Lesson 4: Comparing and Contrasting Different Data Structures, Formats, and Markup Languages |
5. Lesson 5: Explaining Data Integration and Collection Methods |
6. Lesson 6: Identifying Common Reasons for Cleansing and Profiling Data |
7. Lesson 7: Executing Different Data Manipulation Techniques |
8. Lesson 8: Explaining Common Techniques for Data Manipulation and Optimization |
9. Lesson 9: Applying Descriptive Statistical Methods |
10. Lesson 10: Describing Key Analysis Techniques |
11. Lesson 11: Understanding the Use of Different Statistical Methods |
12. Lesson 12: Using the Appropriate Type of Visualization |
13. Lesson 13: Expressing Business Requirements in a Report Format |
14. Lesson 14: Designing Components for Reports and Dashboards |
15. Lesson 15: Distinguishing Different Report Types |
16. Lesson 16: Summarizing the Importance of Data Governance |
17. Lesson 17: Applying Quality Control to Data |
18. Lesson 18: Explaining Master Data Management Concepts |