Clean Data in Google Sheets With Sheets AI Assistant

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Key Takeaways


What Is Data Cleaning in Google Sheets?

Data cleaning in spreadsheets used to mean switching between tools, copying data back and forth or manually editing cells. Flookup brings powerful data cleaning capabilities directly into your spreadsheet workflow through the Data Processing Functions menu.

Instead of manually reviewing each row, you apply functions from the Data Processing menu to clean, standardise and match your data. Results update when your source data changes, making your cleaning workflow repeatable and auditable.


Step 1: Standardise Your Text

Flookup provides a suite of functions accessible through the Data Processing menu. Here are the essentials:

Step 2: Find Fuzzy Matches Across Sheets

The Fuzzy Match function finds the best match for a value in a lookup table, even when there are spelling variations or typos. Access it from the Data Processing menu and configure the source range, lookup range and similarity threshold.

Example: You have a list of company names in one column and a master list in another. To find the industry for "Acme Corp" (even if the master list has "Acme Corporation"), run the Fuzzy Match function with an 85 per cent similarity threshold. The function returns the industry along with a confidence score.

Text Standardisation

The Text Standardisation function cleans text by removing diacritics, punctuation, stop words or extracting domains from URLs. Access it from the Data Processing menu.

Example: Clean a column of addresses by removing punctuation and diacritics. The function processes every cell in the selected range in one pass.

Step 3: Remove Duplicate Entries

The Deduplication function removes duplicate rows based on fuzzy similarity, not just exact matches. Configure the similarity threshold to control how strict the matching is.

Example: Remove duplicate customer names from a list, keeping the first occurrence of each. The function compares every row and consolidates matches above your chosen threshold.

Similarity Scoring

The Similarity Scoring function calculates how similar two text strings are, returning a score from 0 to 1. Use it to audit match quality after deduplication or fuzzy matching.

Example: Compare two product descriptions to verify they refer to the same item before merging records.

Unique List Extraction

The Unique List function extracts unique values from a list, treating similar entries as duplicates. Configure the similarity threshold to control grouping.

Example: Get a unique list of city names, treating "New York" and "NYC" as the same location.


Your AI-Powered Assistant

The Sheets AI Assistant is your AI-powered assistant for building the right functions. Instead of navigating the Data Processing menu or figuring out which function to use, you simply describe what you want to achieve.

How It Works

  1. Describe your goal: Tell the assistant what you want to accomplish in plain language. For example: "I need to match customer names from my sales data against a master customer list, even when there are spelling differences."
  2. Get a function suggestion: The assistant analyzes your request and suggests the appropriate Flookup function for your task.
  3. Refine if needed: If the suggestion is not quite right, ask follow-up questions or provide more context.

When to Use the Assistant

Access the Sheets AI Assistant via Extensions > Flookup Data Wrangler > Sheets AI Assistant in your Google Sheets menu.


Practical Examples

Example 1: Reconciling Vendor Lists

Scenario: You have a list of vendor names from invoices and a master vendor database with name and vendor ID. You need to match each invoice vendor to the correct ID.

Solution: Use the Fuzzy Match function from the Data Processing menu. Select your invoice vendor names as the source and the master database as the lookup range. Set the similarity threshold to 85 per cent. The function returns the vendor ID with a confidence score for every matched row.

Example 2: Cleaning Contact Data

Scenario: You imported contact data from multiple sources and need to standardize phone numbers and remove duplicates.

Solution:

  1. First, run the Text Standardisation function to remove punctuation and diacritics across the affected columns.
  2. Then run the Deduplication function to remove near-duplicate rows above a 90 per cent similarity threshold.

Example 3: Finding Similar Products

Scenario: You have two product catalogs from different suppliers and need to identify which products are the same despite different naming conventions.

Solution: Use the Similarity Scoring function from the Data Processing menu. Select the two product description columns. The function returns a similarity score for each row. Products with scores above 0.8 are likely the same item.


Workflow Tips

Start with the Demo

Before installing Flookup, try all the features in our live demo spreadsheet. No installation or account required.

Use the Right Threshold

The similarity threshold controls how strict the matching is. Lower values find more matches but may include false positives. Higher values are more precise but may miss valid matches. Start with a mid-range threshold and adjust based on your results.

Standardise Before Matching

For best results, clean your text data before performing fuzzy matching. Run the Text Standardisation function to remove punctuation, diacritics and extra spaces. This improves matching accuracy significantly.

Process in Batches

For very large datasets (10,000+ rows), process data in batches or use the Schedule Functions feature for automated processing.


Getting Started

Installation

  1. Install the Flookup Data Wrangler add-on from the Google Workspace Marketplace.
  2. Open your Google Sheet and go to Extensions > Flookup Data Wrangler > Account Management > Profile activation.
  3. Enter your Profile ID to activate your plan.
  4. Start using Flookup's Data Processing Functions.

Try Before You Buy

Explore all features in our live demo spreadsheet. No installation, no credit card needed.

Ready to Clean Your Data?

Get started with the Data Processing Functions and the Sheets AI Assistant to clean, standardise and match your data.


Frequently Asked Questions

How does the Sheets AI Assistant work?

The Sheets AI Assistant is an AI assistant that helps you work with Flookup's Data Processing Functions. You describe what you want to achieve in plain language and it suggests the appropriate function to accomplish your goal.

Do I need to install anything to use Flookup?

Yes, you need to install the Flookup Data Wrangler add-on from the Google Workspace Marketplace. Once installed, all functions become available in the Data Processing menu. You can try them first in our live demo without installation.


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