CompTIA Data+ (DATA+)


Course Overview

As the importance of data analytics grows, more job roles are required to set a context and better communicate vital business intelligence. Collecting, analysing, and reporting data can drive priorities and lead business decision-making. CompTIA Data+ certification validates professionals have the skills required to facilitate data-driven business decisions, including:

  • Mining data
  • Manipulating data
  • Visualising and reporting data
  • Applying basic statistical methods
  • Analysing complex datasets while adhering to governance and quality standards throughout the entire data life cycle

Examination Information

  • CompTIA DA0-001
  • Testing through Pearson VUE


  • CompTIA recommends 18–24 months of experience in a report/business analyst job to succeed in this course.
  • Exposure to databases and analytical tools, a basic understanding of statistics, and data visualisation experiences, such as Excel, Power BI, and Tableau.

Course Objectives

In this CompTIA Data+ course, you will learn:

  • Instruction from CompTIA approved Data+ Certification preparation course.
  • Receive a CompTIA Data+ Exam Voucher included upon completion of the course.
  • Identify Data Concepts and Environments important in analytics.
  • Execute techniques in Data Mining, Data Mining, and Visualisation.
  • Summarise the importance of Data Governance, Quality, and Controls.
  • Continue learning and face new challenges with after-course one-on-one instructor coaching.

Outline: CompTIA Data+ (DATA+)

Module 1: Identifying Basic Concepts of Data Schemas

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

Module 2: Understanding Different Data Systems

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

Module 3: Understanding Types and Characteristics of Data

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

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

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

Module 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

Module 6: Identifying Common Reasons for Cleansing and Profiling Data

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

Module 7: Executing Different Data Manipulation Techniques

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

Module 8: Explaining Common Techniques for Data Manipulation and Optimisation

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

Module 9: Applying Descriptive Statistical Methods

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

Module 10: Describing Key Analysis Techniques

  • Get Started with Analysis
  • Recognise Types of Analysis

Module 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

Module 12: Using the Appropriate Type of Visualisation

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

Module 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

Module 14: Designing Components for Reports and Dashboards

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

Module 15: Distinguishing Different Report Types

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

Module 16: Summarising the Importance of Data Governance

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

Module 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

Module 18: Explaining Master Data Management Concepts

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

Prices & Delivery methods

Online Training

5 days

  • Online Training: CAD 3,265
  • Online Training: US$ 2,475
Classroom Training

5 days

  • Canada: CAD 3,265

Click on town name or "Online Training" to book Schedule

This is an Instructor-Led Classroom course
Guaranteed date:   We will carry out all guaranteed training regardless of the number of attendees, exempt from force majeure or other unexpected events, like e.g. accidents or illness of the trainer, which prevent the course from being conducted.
Instructor-led Online Training:   This computer icon in the schedule indicates that this date/time will be conducted as Instructor-Led Online Training.
This is a FLEX course, which is delivered both virtually and in the classroom.
*   This class is delivered by a partner.

United States

Guaranteed to Run Online Training 09:00 US/Eastern * Enroll
Online Training 09:00 US/Eastern * Enroll
Online Training 09:00 US/Eastern * Enroll