CompTIA Data+

$2,495.00 USD

5 Days


Delivery Methods
Virtual Instructor Led
Private Group

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Course Overview

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 Objectives

On course completion, participants will be able to:
  • Mining data
  • Manipulating data
  • Visualizing and reporting data
  • Applying basic statistical methods
  • Analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle
    • Top-rated instructors: Our crew of subject matter experts have an average instructor rating of 4.8 out of 5 across thousands of reviews.
    • Authorized content: We maintain more than 35 Authorized Training Partnerships with the top players in tech, ensuring your course materials contain the most relevant and up-to date information.
    • Interactive classroom participation: Our virtual training includes live lectures, demonstrations and virtual labs that allow you to participate in discussions with your instructor and fellow classmates to get real-time feedback.
    • Post Class Resources: Review your class content, catch up on any material you may have missed or perfect your new skills with access to resources after your course is complete.
    • Private Group Training: Let our world-class instructors deliver exclusive training courses just for your employees. Our private group training is designed to promote your team’s shared growth and skill development.
    • Tailored Training Solutions: Our subject matter experts can customize the class to specifically address the unique goals of your team.

    Learning Credits: Learning Credits can be purchased well in advance of your training date to avoid having to commit to specific courses or dates. Learning Credits allow you to secure your training budget for an entire year while eliminating the administrative headache of paying for individual classes. They can also be redeemed for a full year from the date of purchase. If you have previously purchased a Learning Credit agreement with New Horizons, you may use a portion of your agreement to pay for this class.

    If you have questions about Learning Credits, please contact your Account Manager.

    Corporate Tech Pass: Our Corporate Tech Pass includes unlimited attendance for a single person, in the following Virtual Instructor Led course types: Microsoft Office, Microsoft Technical, CompTIA, Project Management, SharePoint, ITIL, Certified Ethical Hacker, Certified Hacking Forensics Investigator, Java, Professional Development Courses and more. The full list of eligible course titles can be found at

    If you have questions about our Corporate Tech Pass, please contact your Account Manager.

    Course Prerequisites

    There are no prerequisites for this course.


    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

    Upcoming Class Dates and Times

    Sep 9, 10, 11, 12, 13
    8:00 AM - 4:00 PM
    ENROLL $2,495.00 USD
    Dec 2, 3, 4, 5, 6
    8:00 AM - 4:00 PM
    ENROLL $2,495.00 USD

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