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CompTIA Data Analysis Essentials V1
5 Based on 213 reviews- 334,895 Learners
- 287 Courses
CompTIA Data Analysis Essentials is a focused course that guides learners through a practical data-analysis workflow, from defining a business objective and structuring source data to cleaning, combining, analyzing, visualizing, validating, and sharing results. Learners practice with common metrics, data types, formulas, pivot tables, charts, slicers, dashboards, and data-protection techniques.
Request More InfoClass Price
$99.00
Schedule To Be Announced- VILT
The course uses practice activities and an applied case study to help learners translate business questions into data definitions, identify trends, create reusable calculations, and package analysis for handoff.
- Define an analysis objective and translate business questions into data definitions.
- Identify needed datasets, sources, metrics, data types, and formats.
- Import, structure, clean, reshape, join, and stack data.
- Apply aggregate calculations, descriptive formulas, conditional logic, dynamic formulas, and named ranges.
- Summarize data using pivot tables and communicate findings using appropriate charts.
- Build interactive dashboards using pivots, charts, and slicers.
- Validate data, identify errors, and mask sensitive information.
- Document, package, export, permission, and hand off analysis results.
Virtual Instructor-Led Training
1 days / 8 hours
Who should attend CompTIA Data Analysis Essentials V1 Course
- Professionals who work with business data and spreadsheets
- Business analysts, operations professionals, and project team members
- Marketing, sales, finance, and administrative professionals responsible for reporting
- Early-career data professionals seeking a practical workflow foundation
- Anyone who needs to clean, analyze, visualize, and share data effectively
Prerequisites for CompTIA Data Analysis Essentials V1 Course
CompTIA Data Analysis Essentials V1 Course Outline
- Getting Started
- Course Introduction
- How to Use This Course
- Activity: Pre-Assessment
- Setting Up Your Data Project
- Defining the Analysis Objective
- Why Defining Your Objective is Critical...and Hard
- Turning Business Questions Into Data Definitions
- Practice: Translating Two Business Questions
- Identifying Needed Datasets and Sources
- Common Metrics and Data Sources
- Identify Key Metrics and Sources
- Case Study Introduction
- Case Study: Defining a Data Project
- Importing and Structuring Data
- Importing Data
- Converting Raw Data into Tables and Ranges
- Understanding Different Data Types
- Set Correct Data Types and Formats
- Case Study: Import Data
- Module 2 Review
- Cleaning Data
- Introduction to Cleaning Data
- Common Data Issues
- Practice Cleaning Data
- Case Study: Cleaning the Dataset
- Reshaping Your Data to be Useful
- Introduction to Reshaping Data
- Common Scenarios for Reshaping Columns
- Activity: When to Reshape Columns
- Practice: Reshaping Data
- Case Study: Reshaping the Data
- Combining Datasets
- Introduction to Combining Data Sets
- Practice: Joining Data
- Common Joining Errors
- Stacking Data
- Case Study: Join Datasets
- Module 3 Review
- Aggregate and Descriptive Calculations
- Introduction to Aggregate and Descriptive Calculations
- Common Aggregate and Descriptive Formulas
- Using Aggregate and Descriptive Calculations
- Case Study: Find Key Metrics and Trends
- Conditional Logic
- Introduction to Conditional Logic
- Common Logic Scenarios
- Activity: Common Logic Scenarios
- Practice: Using Conditional Logic
- Case Study: Applying Conditional Logic
- Dynamic Formulas and Named Ranges
- Introduction to Dynamic Formulas
- Reference Guide
- Creating Reusable Formulas
- Case Study: Build Reusable Calc Set
- Module 4 Review
- Pivot Tables
- Introduction to Pivot Tables
- When to Use Pivots vs. Simple Totals
- Activity: Building a Pivot Table
- Practice: Using Pivot Tables
- Case Study: Explore Data with Pivots and Charts
- Standard Charts and Customization
- Introduction to Charts
- Chart Selection and Design Checklist
- Activity: Explore Different Types of Charts
- Practice Creating Charts
- Case Study: Building Charts
- Interactive Dashboards with Slicers
- Introduction to Interactive Dashboards
- Dashboard and Slicer Best Practices
- Combine Pivots, Charts, and Slicers
- Case Study: Build an Interactive Dashboard
- Module 5 Review
- Validate and Safeguard Data
- Introduction to Validating and Protecting Data
- Practice: Validation Rules and Quick Masking
- Case Study: Spot and Fix Errors
- Practice: Identify and Mask Sensitive Data
- Document, Package and Share Results
- Documenting and Sharing Your Analysis
- Export Dashboard, Set Permissions
- Practice: Package and Hand-Off Analysis
- Module 6 Review
