CompTIA Data+

1 – Identifying Basic Concepts of Data Schemas

• Identify Relational and Non-Relational Databases
• Understand the Way We Use Tables, Primary Keys, and Normalization

2 – Understanding Different Data Systems

• Describe Types of Data Processing and Storage Systems
• Explain How Data Changes

3 – Understanding Types and Characteristics of Data

• Understand Types of Data
• Break Down the Field Data Types

4 – Comparing and Contrasting Different Data Structures, Formats, and Markup Languages

• Differentiate between Structured Data and Unstructured Data
• Recognize Different File Formats
• Understand the Different Code Languages Used for Data

5 – Explaining Data Integration and Collection Methods

• Understand the Processes of Extracting, Transforming, and Loading Data
• Explain API/Web Scraping and Other Collection Methods
• Collect and Use Public and Publicly-Available Data
• Use and Collect Survey Data

6 – Identifying Common Reasons for Cleansing and Profiling Data

• Learn to Profile Data
• Address Redundant, Duplicated, and Unnecessary Data
• Work with Missing Value
• Address Invalid Data
• Convert Data to Meet Specifications

7 – Executing Different Data Manipulation Techniques

• Manipulate Field Data and Create Variables
• Transpose and Append Data
• Query Data

8 – Explaining Common Techniques for Data Manipulation and Optimization

• Use Functions to Manipulate Data
• Use Common Techniques for Query Optimization

9 – Applying Descriptive Statistical Methods

• Use Measures of Central Tendency
• Use Measures of Dispersion
• Use Frequency and Percentages

10 – Describing Key Analysis Techniques

• Get Started with Analysis
• Recognize Types of Analysis

11 – Understanding the Use of Different Statistical Methods

• Understand the Importance of Statistical Tests
• Break Down the Hypothesis Test
• Understand Tests and Methods to Determine Relationships Between Variables

12 – Using the Appropriate Type of Visualization

• Use Basic Visuals
• Build Advanced Visuals
• Build Maps with Geographical Data
• Use Visuals to Tell a Story

13 – Expressing Business Requirements in a Report Format

• Consider Audience Needs When Developing a Report
• Describe Data Source Considerations For Reporting
• Describe Considerations for Delivering Reports and Dashboards
• Develop Reports or Dashboards
• Understand Ways to Sort and Filter Data

14 – Designing Components for Reports and Dashboards

• Design Elements for Reports and Dashboards
• Utilize Standard Elements
• Creating a Narrative and Other Written Elements
• Understand Deployment Considerations

15 – Understand Deployment Considerations

• Understand How Updates and Timing Affect Reporting
• Differentiate Between Types of Reports

16 – Summarizing the Importance of Data Governance

• Define Data Governance
• Understand Access Requirements and Policies
• Understand Security Requirements
• Understand Entity Relationship Requirements

17 – Applying Quality Control to Data

• Describe Characteristics, Rules, and Metrics of Data Quality
• Identify Reasons to Quality Check Data and Methods of Data Validation

18 – Explaining Master Data Management Concepts

• Explain the Basics of Master Data Management
• Describe Master Data Management Processes