Data Cleaning and Preparation in Excel
Master data cleaning and preparation in Excel to organize, refine, and analyze data efficiently for accurate insights and smarter decisions.
October
27,
2025
12:00 PM - 02:00 PM (Eastern Time)
Duration: 1 Day
Hours: 2 Hours
Training Level: All Levels
About the course:
Accurate and reliable data is the foundation of effective analysis and decision-making. This course, “Data Cleaning and Preparation in Excel,” equips participants with hands-on skills to transform messy, inconsistent, or incomplete data into high-quality datasets ready for analysis. Using real-world examples and practical exercises, participants will learn the essential tools, formulas, and best practices in Excel to efficiently clean, validate, and prepare data for reporting or analytics projects.
Course Objectives:
By the end of this course, participants will be able to:
- Understand the importance of data cleaning and preparation in analytics.
- Identify common data quality issues and inconsistencies.
- Use Excel functions and features to clean, transform, and validate data.
- Apply practical techniques for handling duplicates, missing values, errors, and outliers.
- Build a workflow for preparing data for analysis or reporting.
Who is the Target Audience?
This course is ideal for:
- Analysts and business professionals working with data in Excel.
- Students and researchers conducting data-driven projects.
- Managers and team leads are responsible for data quality.
- Anyone who wants to enhance their Excel skills for better data handling.
Basic Knowledge:
- No prior advanced Excel knowledge is required.
Curriculum
Total Duration: 2 Hours
Introduction to Data Cleaning
- Why Data Cleaning Matters
- Common Data Issues (duplicates, blanks, inconsistencies, errors)
Inspecting and Understanding Your Data
- Exploring Data Using Excel (sorting, filtering, basic analysis)
- Data Profiling and Initial Assessment
Essential Data Cleaning Techniques
- Removing Duplicates and Handling Blanks
- Finding and Correcting Errors (spelling, formats, data types)
- Standardizing Data (text, numbers, dates)
Practical Tools and Functions
- Using Text Functions (TRIM, UPPER/LOWER, LEFT, RIGHT, FIND, SUBSTITUTE)
- Data Validation and Conditional Formatting
- Flash Fill and Find & Replace
Handling Missing Values and Outliers
- Strategies for Filling or Excluding Missing Data
- Identifying and Addressing Outliers
Preparing Data for Analysis
- Structuring Data Tables and Setting Headers
- Converting Data Ranges to Tables
- Creating a Repeatable Data Cleaning Workflow
Hands-On Practice and Q&A
- Cleaning a Sample Dataset Step-by-Step
- Tips, Shortcuts, and Best Practices
- Open Q&A Session