ARSENIY

Dirty data is a common problem faced by businesses of all sizes, as it can lead to incorrect calculations, damage to reputation, and other negative consequences. In this article, we discuss how artificial intelligence (AI) can be used to address dirty data by automating tasks such as data format validation, correction, and gap filling. We also provide an example of using GPT-3, a natural language processing tool, to clean and standardize data. By leveraging the power of AI, businesses can improve the quality of their data and avoid the negative consequences of dirty data... Senior web developer, specializing in data and high load, over a decade in web development, python database expert, team leader project manager, great communicator problem solver