Update using_LLMs_as_a_tool_for_scaling_data_standardization_and_cleaning.md

Author: charrowc

social-impact/genai/using_LLMs_as_a_tool_for_scaling_data_standardization_and_cleaning.md

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-layout: default
+layout: article
 title: Using LLMs as a Tool for Scaling Data Standardization and Cleaning
 subtitle: This article contains pointers for anyone looking to adopt LLMs for data standardization and cleaning tasks. It is a deeper dive into the technical details of one use case, intended for a user that is experimenting with Generative AI.
 date: 02/29/2024
 author: Deborshi Goswami with Jacob Leppek and Rachel Wells
 audience: Social Impact Professionals
 category: social-impact
 subcategory: genai
+previous: setting_up_GenAI_tools_and_technology
+next: resource_hub_for_genAI_in_the_social_sector
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 This article came from a collaboration between DataKind volunteer Deborshi Goswami and Vivery. Onboarding new partners into the Vivery platform requires a lengthy data collection, cleaning, and standardization process. Since each partner stores data in different formats, a “if\-then” rules\-based parsing approach isn’t flexible enough to work across multiple partners. LLMs can assist with the cleaning and standardization process with messy data that isn’t consistent in its formatting.