CompTIA Data Analysis Essentials

This facilitated session uses Microsoft Excel to develop essential data analysis skills that can be applied across a wide range of job roles and industries. Learners will gain the ability to solve problems using data, support ideas with evidence, and make informed decisions with confidence. CompTIA Data Analysis Essentials provides a practical, beginner-friendly introduction to data analysis, focusing on real-world application rather than theory alone.

The facilitated session is designed for individuals with little or no prior experience in data analysis and offers an accessible pathway to building job-ready, resume-boosting skills. Through hands-on activities via Microsoft Excel, guided examples, and applied projects, learners will develop a strong foundation in working with data using common tools and industry-aligned practices.

Prerequisites

A basic working knowledge of Microsoft Excel is needed to complete this course.

Whilst this session is designed for beginners and is accessible to learners with no prior data analysis experience, a basic level of digital literacy, including confidence using a computer and working with simple files, will help learners get the most from the session.

Target Audience

This course is suitable for:

• Individuals new to data analysis who want to build foundational, transferable skills
• Professionals in non-technical roles who work with data and want to improve decision-making
• Career changers exploring entry-level data, analytics, or business intelligence roles
• Students and early-career professionals seeking practical, workplace-relevant skills

On successful completion of this course, learners will be able to:

• Define analysis objectives: Learn how to clarify business questions and set clear success criteria.
• Import and structure data: Work hands-on with real datasets—import, structure, and format information for effective analysis.
• Clean and transform data: Master essential data cleaning methods to ensure your results are accurate and relevant.
• Combine datasets and lookups: Integrate multiple sources and leverage lookup techniques for deeper insights.
• Perform analyses and calculations: Apply core data analysis techniques—calculate statistics, spot trends, and build useful formulas.
• Summarize and visualize data: Create compelling visuals and dashboards to communicate your findings.
• Ensure data integrity and ethics: Learn best practices for data accuracy, privacy, and ethical sharing.

Module 1: Course Introduction

• Topic 1.1: Getting Started

Module 2: Setting Up Your Data Project

• Topic 2.1: Defining the Analysis Objective
• Topic 2.2: Importing and Structuring Data

Module 3: Cleaning and Combining Data

• Topic 3.1: Cleaning Data
• Topic 3.2: Reshaping Your Data to be Useful
• Topic 3.3: Combining Datasets

Module 4: Core Analyses and Calculations

• Topic 4.1: Aggregate and Descriptive Calculations
• Topic 4.2: Conditional Logic
• Topic 4.3: Dynamic Formulas and Named Ranges

Module 5: Summarizing and Visualizing Data

• Topic 5.1: Pivot Tables
• Topic 5.2: Standard Charts and Customization
• Topic 5.3: Interactive Dashboards with Slicers

Module 6: Data Integrity, Ethics and Sharing Results

• Topic 6.1: Validate and Safeguard Data
• Topic 6.2: Document, Package and Share Results

What's included?

• Online platform voucher

Exams and Assessments

This session does not include a formal exam. Learners are assessed through an end-of-course assessment designed to validate understanding and skills gained throughout the learning journey.

On successful completion of the assessment, learners are awarded a CompTIA Competency Certificate (CompCert) - an official way to prove your data analysis proficiency to employers.