You’ve done the hard part. You’ve pulled together a bunch of relevant data to help you make a decision. But when you open the spreadsheet, you realize it’s a mess. There are incorrect entries, duplicate rows, and inconsistent formatting. Cleaning it will take forever. If you’ve been in this situation, you understand how vital data cleaning is to ensuring accurate analysis. But it can also be tedious and time-consuming. Luckily, Excel has several built-in features and functions that can help you clean your data quickly and efficiently. In this guide, we’ll explore how to clean data in Excel, including techniques and tips. We’ll also introduce you to a useful best AI for Excel that can help you automate the process.

Table Of Contents

• How to Get Your Data Ready for Cleaning

• Why It Matters to Clean Data

• Six Methods for Cleaning Data in Excel (Step-by-Step)

• Make Decisions At Scale Through AI With Numerous AI’s Spreadsheet AI Tool

How to Get Your Data Ready for Cleaning

Understand the Dataset: The First Step to Cleaning Data in Excel

Before starting, take time to familiarize yourself with the data. 

Review the Data Source

Identify where the data comes from (e.g., exported from a CRM, manually entered, or scraped from online sources). Understand its purpose and how it will be used, as this will guide the cleaning process. 

Preview the Data

Scroll through the dataset or use the Filter function to check for common issues like blank rows, missing values, or duplicates. 

Pro Tip

Create a checklist of questions to identify what needs cleaning: 

• Are there blank cells? 

• Are all columns adequately labeled? 

• Are there duplicate rows or inconsistencies in formatting? 

Back-Up the Original Data: How to Avoid Losing Your Work

It’s essential to save a copy of your original dataset before making any changes. 

Why It’s Important

You can revert to the original version if an error occurs or data is accidentally deleted during cleaning. 

How to Save a Backup

Save the original file with a clear name, such as Dataset_Original.xlsx. Consider creating a versioning system (e.g., Dataset_V1.xlsx) for multiple iterations. 

Pro Tip

Work on a separate sheet or file while cleaning and keep the raw data untouched. 

Remove Unnecessary Data: How to Clutter-Free Your Dataset

Streamline your dataset by eliminating irrelevant or unnecessary information. 

Delete Extra Rows and Columns

Highlight and delete blank rows or columns that don’t contain meaningful data. Use Ctrl + Shift + Arrow Keys to highlight large sections quickly for deletion. 

Filter Out Irrelevant Data

Use the Filter tool to hide irrelevant rows temporarily or permanently delete them. 

Example

If the dataset contains a "Region" column but you only need data for one region, filter out the others. 

Pro Tip

If unsure whether data is necessary, move it to a temporary sheet instead of deleting it permanently. 

Standardize Column Headers: How to Make Cleaning Data Easier

Ensure your columns are clearly labeled to make cleaning easier. 

Rename Columns

Use descriptive names like "Customer Name" instead of generic ones like "Column A." Double-check for typos or inconsistent naming conventions (e.g., "Order ID" vs. "Order_Number"). 

Remove Special Characters

Use Find and Replace (Ctrl + H) to remove symbols like “#” or “@” from column headers. 

Pro Tip

Use camel or snake case if data is exported for coding purposes (e.g., customer_name or CustomerName). 

Identify Key Cleaning Objectives: How to Set Goals for the Cleaning Process

Define what you need to accomplish in the cleaning process. 

Common Objectives 

• Remove duplicates. 

• Standardize formatting (dates, text, and numbers). 

• Address missing or inconsistent data. 

• Fix errors (e.g., typos, misplaced entries). 

How to Prioritize Cleaning Steps

Start with high-impact issues, such as duplicates or blank cells, that affect data accuracy. Move to less critical tasks, like formatting or reorganizing columns. 

Enable Useful Excel Tools: How to Make Cleaning Data Easier

Activate or familiarize yourself with Excel features that will aid in cleaning. 

Turn on Filter Options

Go to Data > Filter to enable dropdowns for each column, making sorting and identifying issues easier. 

Explore Conditional Formatting

Highlight cells with errors or duplicates using Conditional Formatting under the Home tab. 

Enable Power Query

Power Query in the Data tab simplifies bulk cleaning tasks like merging columns, filtering rows, and reshaping data. 

Pro Tip

If using Excel frequently, customize your Quick Access Toolbar with cleaning tools like Remove Duplicates or Find and Replace. 

Check Data Types and Formats: How to Ensure Your Data is Ready for Cleaning

Ensure all data is in the correct format before cleaning: 

Numbers

Verify that numerical data isn’t stored as text (e.g., 1234 as "1234"). Highlight the column, go to Format Cells, and set it to "Number." 

Dates

Check for inconsistencies in date formats. Highlight the column, right-click, and set it to a uniform format (e.g., "MM/DD/YYYY"). 

Text

Ensure text fields like names or categories follow consistent capitalization and formatting. 

Using Numerous to Simplify Preparation: How to Save Time and Reduce Errors During Data Prep

Numerous can automate many of these preparation steps: 

Prompt Examples

• "Standardize all column headers to camel case." 

• "Identify and remove unnecessary blank rows and columns." 

• "Highlight inconsistent date formats in column [X]." 

Using Numerous saves time and avoids manual errors during the preparation phase.

Related Reading

• Smart Fill Google Sheets
• AI Tools List
• How to Extract Certain Text From a Cell in Excel
• Sheets AI Alternatives
• How to Summarize Data in Excel
• How to Clean Data

Why It Matters to Clean Data

Clean Data Equals Accurate Data

Cleaning data helps ensure accuracy and reliability by eliminating errors and inconsistencies that could skew results and lead to poor decision-making. For example, duplicate entries or typos in sales records can result in incorrect revenue reporting. Inaccurate data can mislead analyses of business performance, customer behavior, or market trends. This can have dire consequences. A marketing campaign that uses correct customer data could target the right audience, wasting resources and reducing ROI. Regularly cleaning and validating data can help ensure it remains a reliable foundation for analysis.

Start Clean to Save Time and Increase Efficiency

Cleaning data upfront helps you avoid wasting time on fixing errors later. Messy data requires extra time for troubleshooting and delaying projects or decisions. Analysts often spend up to 80% of their time cleaning data instead of analyzing it. Clean data allows faster and more accurate reporting, enabling teams to focus on actionable insights rather than manual fixes. Use automation tools like Numerous to speed up repetitive cleaning tasks, saving hours of manual work. 

Clean Data Supports Better Decision-Making

Clean data is the foundation of informed, data-driven decisions. It provides a clear and accurate picture of business performance, customer behavior, or market trends. Clean datasets help businesses identify patterns and opportunities otherwise obscured by messy data. For instance, a clean sales dataset allows managers to pinpoint best-performing products, refine pricing strategies, and allocate resources more effectively. Always validate cleaned data with a test analysis to ensure it aligns with expected results.

Clean Data Builds Professionalism and Credibility

Well-maintained data demonstrates professionalism and builds trust with stakeholders. Clean data reflects a commitment to accuracy and quality, especially when shared with clients, investors, or regulatory bodies. Errors in shared reports or dashboards can harm your reputation and lead to loss of confidence. For example, a financial report with clean, audited data builds credibility with investors, whereas errors can raise red flags. Maintain an audit trail of all changes made during the cleaning process to ensure transparency. 

Clean Data Reduces Risks and Errors

Messy data increases the risk of costly mistakes, especially in financial or operational settings. Misaligned or incorrect data in invoices, contracts, or financial statements can lead to legal or compliance issues. Overlooking duplicate records in a CRM system can result in duplicated efforts by sales teams. Clean data reduces errors in downstream processes like billing, forecasting, or inventory management. It also helps ensure data protection regulations (e.g., GDPR) compliance, reducing potential fines or penalties. Implement regular data cleaning schedules to minimize risks and keep your systems updated.

Clean Data Prepares Your Organization for Automation and Advanced Analytics

Clean data is essential for leveraging automation tools and advanced analytics effectively. For example, clean data ensures smoother integration with tools like Numerous, which can automate workflows such as categorizing, deduplicating, or formatting. A clean dataset of customer reviews can be instantly categorized by sentiment using AI-driven tools. Predictive modeling, machine learning, and AI applications require clean, structured datasets to produce accurate results. For instance, a machine learning algorithm trained on clean customer data can accurately predict churn rates and suggest retention strategies. Use Numerous to automate cleaning tasks and ensure your data is AI-ready.

Clean Data Maximizes ROI on Data-Driven Projects

Clean data enables businesses to extract maximum value from their analytics tools and systems investments. Dirty data diminishes the effectiveness of costly software and analytics tools, leading to wasted resources. Clean data ensures that insights are actionable and aligned with business objectives. For example, clean customer data helps personalize marketing campaigns, increasing engagement and conversion rates, thereby maximizing ROI. Regularly clean and monitor data quality to ensure continued value from analytics tools.

Make Decisions At Scale Through AI With Numerous AI’s Spreadsheet AI Tool

Numerous is an AI-powered tool that enables content marketers, Ecommerce businesses, and more to do tasks many times over through AI, like writing SEO blog posts, generating hashtags, mass categorizing products with sentiment analysis and classification, and many more things by simply dragging down a cell in a spreadsheet. With a simple prompt, Numerous returns any spreadsheet function, simple or complex, within seconds. The capabilities of Numerous are endless. It is versatile and can be used with Microsoft Excel and Google Sheets. Get started today with Numerous.ai so that you can make business decisions at scale using AI in both Google Sheets and Microsoft Excel. Learn more about how you can 10x your marketing efforts with Numerous’s ChatGPT for spreadsheets tool.

Six Methods for Cleaning Data in Excel (Step-by-Step)

1. Remove Duplicates

Eliminating repeated rows or entries can skew results. Select the dataset you want to clean, ensuring you include all columns necessary for identifying duplicates. Head to the Data tab on the Ribbon and click Remove Duplicates. In the dialog box, select the columns to check for duplicates. For example, select both columns if a combination of “Name” and “Email” identifies unique entries. Click OK, and Excel displays how many duplicates were removed and how many unique entries remain.  

Pro Tip

Always keep a backup of your original dataset before removing duplicates in case you need to cross-verify or undo the changes.  

2. Fix Blank Cells

Replacing empty cells with meaningful data or placeholders can prevent analysis errors. To kick off, highlight the dataset or specific column you want to clean. Next, use Ctrl + G (Go To Special), select Special > Blanks, and click OK to highlight all blank cells. Choose a suitable replacement for the blank cells: For text, enter placeholders like "N/A" or "Missing." Use formulas such as =AVERAGE(column_range) to calculate a reasonable number-value. For dates, fill in the blanks with a default or approximate date, depending on the context. Finally, press Ctrl + Enter to apply the changes to all selected blank cells.  

Pro Tip

Avoid leaving blanks untreated, as they can disrupt formulas or lead to incomplete results during analysis.  

3. Standardize Formatting

Ensuring consistency across the dataset promotes better readability and analysis. For text formatting, use =UPPER(), =LOWER(), or =PROPER() to standardize text capitalization. For example, transform "John Doe" into "John Doe" using =PROPER(A1). Next, apply consistent abbreviations or naming conventions across columns (e.g., “NY” for New York). For date formatting, highlight the date column, right-click, and select Format Cells. Depending on your region, choose a standard format like DD/MM/YYYY or MM/DD/YYYY. For number formatting, highlight numerical columns, right-click, and select Format Cells > Number to ensure consistency in decimal places, currency symbols, or percentages.  

Pro Tip

Use the Format Painter (in the Home tab) to apply consistent formatting across multiple cells or columns quickly.  

4. Eliminate Extra Spaces and Characters

Cleaning up messy text entries removes unnecessary spaces, symbols, and non-standard characters. Start using the =TRIM() function to remove leading, trailing, and extra spaces from text. For example: =TRIM(A1) cleans up " John Doe " into "John Doe." Next, use the Find and Replace tool (Ctrl + H): Replace unwanted characters (e.g., “$” or “#”) with a blank space or remove them entirely. For advanced replacements, use =SUBSTITUTE() to replace specific text or symbols. For example: =SUBSTITUTE(A1, "-", "") removes dashes from phone numbers.  

Pro Tip

After cleaning, double-check formatting by sorting or filtering the column to catch any overlooked inconsistencies.  

5. Use Power Query for Advanced Cleaning

Automating complex cleaning tasks with Excel’s built-in Power Query tool saves time and improves accuracy. Go to Data > Get & Transform Data > Launch Power Query Editor to get started. Import your dataset by selecting your Excel range or table. Apply transformations to clean your data. For example, remove duplicates using the Remove Rows > Remove Duplicates option. You can also split the text into columns using Split Column by Delimiter for fields like “First Name, Last Name.” Group data for summaries or reorganize rows as needed. Once finished, click Close & Load to save the cleaned dataset into Excel.  

Pro Tip

Save your Power Query steps as a reusable script to clean similar datasets in the future without repeating manual processes.  

6. Automate Data Cleaning with Numerous

Simplifying and accelerating repetitive cleaning tasks using AI-powered automation improves efficiency and accuracy. For example, to remove duplicates, prompt: "Remove all duplicate rows based on columns [X, Y, Z]." To fill blank cells, prompt: "Replace all blank cells in column [X] with 'N/A' or the average value." To standardize formats, prompt: "Standardize all dates in DD/MM/YYYY format and capitalize names in column [X]." To trim spaces and replace characters, prompt: "Remove extra spaces and dashes from phone numbers in column [X]." To perform advanced transformations, prompt: "Split full names in column [X] into separate first and last name columns."  

Pro Tip

Numerous allow you to automate even complex Excel functions, saving hours of manual effort and reducing errors.  

Related Reading

• Unstructured Data Processing
• Best Data Cleaning Tools
• AI for Data Cleaning
• ChatGPT for Data Analysis
• Using AI to Analyze Data
• Automated Data Cleaning Excel
• AI Data Processing
• ChatGPT Summarize Text

Make Decisions At Scale Through AI With Numerous AI’s Spreadsheet AI Tool

Numerous is an AI-powered tool that enables content marketers, Ecommerce businesses, and more to do tasks many times over through AI, like writing SEO blog posts, generating hashtags, mass categorizing products with sentiment analysis and classification, and many more things by simply dragging down a cell in a spreadsheet. With a simple prompt, Numerous returns any spreadsheet function, simple or complex, within seconds. 

The capabilities of Numerous are endless. It is versatile and can be used with Microsoft Excel and Google Sheets. Get started today with Numerous.ai so that you can make business decisions at scale using AI in both Google Sheets and Microsoft Excel. Learn more about how you can 10x your marketing efforts with Numerous’s ChatGPT for spreadsheets tool.

Related Reading

• Automated Data Cleaning
• How to Use ChatGPT in Excel
• Use AI to Rewrite Text
• Data Cleaning AI
• Summarize Written Text
• ChatGPT Rewriter
• AI Rewriting Tool