CompTIA Data+
1. Understanding Fundamentals of Data Schemas
– Differentiating Relational and Non-Relational Databases
– Comprehending Table Structures, Primary Keys, and Normalization
2. Exploring Data Systems
– Describing Various Data Processing and Storage Systems
– Explaining Data Modification Processes
3. Understanding Types and Characteristics of Data
– Recognizing Data Categories
– Analyzing Field Data Types
4. Contrasting Data Structures, Formats, and Markup Languages
– Distinguishing between Structured and Unstructured Data
– Identifying Different File Formats and Code Languages Used for Data
5. Exploring Data Integration and Collection Methods
– Understanding Data Extraction, Transformation, and Loading Processes
– Explaining API/Web Scraping and Other Collection Methods
– Utilizing Public and Publicly-Available Data
– Gathering and Utilizing Survey Data
6. Identifying Data Cleansing and Profiling Techniques
– Profiling Data and Identifying Anomalies
– Addressing Redundant, Duplicated, and Unnecessary Data
– Handling Missing and Invalid Data
– Converting Data to Meet Specifications
7. Executing Data Manipulation Techniques
– Manipulating Field Data and Creating Variables
– Performing Data Transposition and Appending
– Querying Data
8. Exploring Data Manipulation and Optimization
– Utilizing Functions for Data Manipulation
– Implementing Common Techniques for Query Optimization
9. Applying Descriptive Statistical Methods
– Using Measures of Central Tendency and Dispersion
– Analyzing Data Frequency and Percentages
10. Describing Key Analysis Techniques
– Introduction to Data Analysis
– Recognizing Different Analysis Types
11. Understanding Statistical Methods
– Importance of Statistical Tests
– Understanding Hypothesis Testing
– Exploring Methods to Determine Relationships Between Variables
12. Utilizing Data Visualization
– Creating Basic and Advanced Visuals
– Building Geographical Data Maps
– Using Visuals to Convey Information
13. Expressing Business Requirements in Reports
– Considering Audience Needs for Report Development
– Addressing Data Source Considerations
– Developing Reports and Dashboards
– Implementing Data Sorting and Filtering
14. Designing Components for Reports and Dashboards
– Designing Standard Elements
– Incorporating Narrative and Written Elements
– Understanding Deployment Considerations
15. Understanding Report Deployment
– Timing and Update Considerations
– Different Types of Reports
16. Summarizing Data Governance
– Defining Data Governance
– Understanding Access, Security, and Entity Relationship Requirements
17. Applying Quality Control to Data
– Describing Data Quality Characteristics, Rules, and Metrics
– Identifying Reasons and Methods for Data Validation
18. Exploring Master Data Management Concepts
– Basics of Master Data Management
– Describing Master Data Management Processes