Data cleansing with generative AI
Convert text data in Excel to numerical values and categorical values using Azure OpenAI and Python!
This article introduces a method using Azure OpenAI services and Python to format (cleanse) long text data for analysis. It processes text data from surveys, product reviews, complaints, and emails to extract specified elements and convert them into numerical values or categories. The structure involves using three components: Excel files, Azure OpenAI, and Python. It explains the steps for creating a resource group in Azure, creating an AOAI resource, configuring the AOAI network, deploying a generative AI model, creating functions to call the generative AI model in Python, reading and processing the Excel file, and outputting the results. As a reference, the cost for processing approximately 1,000 data entries with gpt-4o-mini is 47 yen, which is deemed sufficient for data cleansing. *For detailed content of the blog, please refer to the related links. For more information, feel free to contact us.*
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CNS Corporation is a company engaged in system engineering services. A high-level group of engineers provides services in areas such as big data, cloud, AI, finance, retail, infrastructure development, and system development. In addition to engineering services, we offer consulting focused on realizing our clients' management strategies and business transformations, as well as services centered on business operations and system operations, creating new value that advances society.
