INTELLIGENT DATA CLEANING FOR GOOGLE SHEETS

Harness the Power of AI Data Cleaning

Flookup AI revolutionizes data cleaning in Google Sheets by leveraging advanced artificial intelligence. Our AI-powered features go beyond traditional methods, enabling you to clean, standardize and enrich your datasets with unprecedented accuracy and efficiency. Discover how semantic matching and intelligent data standardization can transform your data analysis workflows.

Introduction to Semantic Matching

Semantic matching allows you to compare text based on its meaning rather than just its surface-level similarity. This is useful for finding matches between texts that are conceptually similar but use different wording.
Please note that all the functions discussed herein are accessible under Extensions > Flookup Data Wrangler > Intelligent functions via your spreadsheet menu.

Compare Text by Semantic Similarity

1. Open the sidebar
   Navigate to the Semantic comparison tool within the Flookup Data Wrangler sidebar.
2. Select the range containing the lookup value
   Highlight a single column and click Grab selected range.
3. Select a second range to compare
   Highlight another single column and click Grab selected range.
4. Specify output location
   Click an empty cell to mark where the results should appear.
5. Get fuzzy matches
   Click the Get semantic similarities button.

Notes on Comparing Text by Semantic Similarity

• Matches reflect meaning, not just surface similarity e.g. “I love dogs” versus “I adore canines”.
• Only the first column of each selected range is used; ensure relevant text is in that column.
• This feature consumes credits. Your processing limit is determined by your available credit balance.

Fuzzy Match by Semantic Similarity

1. Open the sidebar
   Navigate to the Semantic matching tool within the Flookup Data Wrangler sidebar.
2. Select the range containing the lookup value
   Highlight a single column of data and click Grab selected range to read it into Primary range.
3. Select the range where the lookup is potentially located
   Highlight a separate range of one or more columns and click Grab selected range to read it into Secondary range.
4. Specify the lookup column
   Enter the index of the column in Secondary range to compare with values in Primary range.
5. Specify the return column
   Enter the index of the column in Secondary range from which you want values to be returned.
6. Specify output location
   Click an empty cell within the spreadsheet to mark the position where the results should be displayed.
7. Get fuzzy matches
   Click the Get semantic matches button to finish.

Notes on Fuzzy Matching by Semantic Similarity

• Lookup_column only processes one column. If you select more than one, only the leftmost will be analysed.
• For best results, correct spelling errors before running this function.
  Head to Tools > Spelling > Spell check in the spreadsheet menu.

Benefits of Semantic Matching

Semantic matching helps you discover underlying relationships in your data that are not apparent from simple text comparisons. This feature allows you to clean, standardize and enrich your datasets with improved accuracy and efficiency. Get started with Flookup Data Wrangler to enhance your data analysis.

Introduction to Standardizing Data with AI

Leverage the power of clean data with Flookup AI's "Standardize Data" feature, an essential tool for effective data standardization and text normalization within Google Sheets.

Flookup AI leverages advanced AI capabilities to perform sophisticated data cleaning tasks, offering more dynamic and context-aware data manipulation. This mode is ideal for complex standardization, transformation, imputation and consolidation tasks.

How to Use the AI Standardization Functions

These functions are designed to help you with various data cleaning tasks. You can access them through the Flookup Data Wrangler extension in your spreadsheet menu.

• Standardize: Applies common standardization practices, including consistent casing, trimming spaces, correcting misspellings and formatting numeric values.
• Transform: Transforms data based on user-specified instructions, such as converting date formats or changing measurement units.
• Impute: Fills in missing values using appropriate imputation strategies like mean, median or mode.
• Consolidate: Detects and removes outliers from the dataset using statistical methods.

1. Open the sidebar
   Navigate to the Intelligent standardization section within the Flookup Data Wrangler sidebar.
2. Select the function to run
   Choose the specific Intelligent Mode function from the available options.
3. Select the range to process
   Highlight the column of data you wish to process and click Grab selected range.
4. Specify output location
   Click an empty cell to mark where the results should appear.
5. Run the function
   Click the Submit data cleaning prompt button to finish.

You Might Also Like

• The Complete Guide to AI-Powered Data Cleaning
• How to Compare Text for Similarity
• How to Fuzzy Match Data by Text Similarity
• Highlighting Duplicates by Text Similarity
• Removing Duplicates by Text Similarity