CompTIA Data+

CompTIA Data+ (CTIA_DATA)

Course Length: 5 days
Delivery Methods: Multiple delivery options
Course Overview
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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.

Course Benefits
  • Learn to mine valuable insights from diverse datasets.
  • Understand the principles of data manipulation to meet analytical needs.
  • Get experience with creating impactful visualizations and comprehensive reports.
  • Understand basic statistical methods for data-driven decision-making.
  • Learn to analyze complex datasets while adhering to governance and quality standards throughout the data lifecycle.
Available Delivery Methods
Public Class
Public expert-led online training from the convenience of your home, office or anywhere with an internet connection. Guaranteed to run .
Private Class
Private classes are delivered for groups at your offices or a location of your choice.
Course Outline
  1. Identifying Basic Concepts of Data Schemas
    1. Identify Relational and Non-Relational Databases
    2. Understand the Way We Use Tables, Primary Keys, and Normalization
  2. Understanding Different Data Systems
    1. Describe Types of Data Processing and Storage Systems
    2. Explain How Data Changes
  3. Understanding Types and Characteristics of Data
    1. Understand Types of Data
    2. Break Down the Field Data Types
  4. Comparing and Contrasting Different Data Structures, Formats, and Markup Languages
    1. Differentiate between Structured Data and Unstructured Data
    2. Recognize Different File Formats
    3. Understand the Different Code Languages Used for Data
  5. Explaining Data Integration and Collection Methods
    1. Understand the Processes of Extracting, Transforming, and Loading Data
    2. Explain API/Web Scraping and Other Collection Methods
    3. Collect and Use Public and Publicly-Available Data
    4. Use and Collect Survey Data
  6. Identifying Common Reasons for Cleansing and Profiling Data
    1. Learn to Profile Data
    2. Address Redundant, Duplicated, and Unnecessary Data
    3. Work with Missing Value
    4. Address Invalid Data
    5. Convert Data to Meet Specifications
  7. Executing Different Data Manipulation Techniques
    1. Manipulate Field Data and Create Variables
    2. Transpose and Append Data
    3. Query Data
  8. Explaining Common Techniques for Data Manipulation and Optimization
    1. Use Functions to Manipulate Data
    2. Use Common Techniques for Query Optimization
  9. Applying Descriptive Statistical Methods
    1. Use Measures of Central Tendency
    2. Use Measures of Dispersion
    3. Use Frequency and Percentages
  10. Describing Key Analysis Techniques
    1. Get Started with Analysis
    2. Recognize Types of Analysis
  11. Understanding the Use of Different Statistical Methods
    1. Understand the Importance of Statistical Tests
    2. Break Down the Hypothesis Test
    3. Understand Tests and Methods to Determine Relationships Between Variables
  12. Using the Appropriate Type of Visualization
    1. Use Basic Visuals
    2. Build Advanced Visuals
    3. Build Maps with Geographical Data
    4. Use Visuals to Tell a Story
  13. Expressing Business Requirements in a Report Format
    1. Consider Audience Needs When Developing a Report
    2. Describe Data Source Considerations For Reporting
    3. Describe Considerations for Delivering Reports and Dashboards
    4. Develop Reports or Dashboards
    5. Understand Ways to Sort and Filter Data
  14. Designing Components for Reports and Dashboards
    1. Design Elements for Reports and Dashboards
    2. Utilize Standard Elements
    3. Creating a Narrative and Other Written Elements
    4. Understand Deployment Considerations
  15. Understand Deployment Considerations
    1. Understand How Updates and Timing Affect Reporting
    2. Differentiate Between Types of Reports
  16. Summarizing the Importance of Data Governance
    1. Define Data Governance
    2. Understand Access Requirements and Policies
    3. Understand Security Requirements
    4. Understand Entity Relationship Requirements
  17. Applying Quality Control to Data
    1. Describe Characteristics, Rules, and Metrics of Data Quality
    2. Identify Reasons to Quality Check Data and Methods of Data Validation
  18. Explaining Master Data Management Concepts
    1. Explain the Basics of Master Data Management
    2. Describe Master Data Management Processes
Class Materials

Each student will receive a comprehensive set of materials, including course notes and all the class examples.

Live Public Class
$2,445.10 / student
Please select a class.
Live Private Class
  • Private Class for your Team
  • Live training
  • Online or On-location
  • Customizable
  • Expert Instructors
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