INTELLIGENT DATA CLEANING FOR GOOGLE SHEETS

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 > Matching and Analysis via your spreadsheet menu.


Compare Text by Semantic Similarity

  1. Open the sidebar
    Navigate to the Compare by meaning 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


Fuzzy Match by Semantic Similarity

  1. Open the sidebar
    Navigate to the Fuzzy match by meaning 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


Benefits of Semantic Matching

Semantic matching represents a significant advancement in data comparison and analysis. Unlike traditional text matching methods that rely on character-by-character comparisons, semantic matching understands the underlying meaning of text. This enables you to identify relationships and patterns that remain invisible to surface-level similarity algorithms.

Key Advantages

Why Semantic Matching Matters for Your Data

Data quality directly impacts business intelligence and decision-making. Organisations often struggle with datasets containing entries described in different ways that refer to the same entity. Traditional deduplication approaches miss these variations, leaving your analysis incomplete. Semantic matching fills this gap by recognizing conceptual equivalence, ensuring your data analysis is comprehensive and trustworthy.


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