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Data cleaning and standardization is a time-consuming and error-prone task. Inaccurate or inconsistent data can lead to biased analysis, incorrect conclusions, and hinder effective decision-making. Manual data cleaning processes are labor-intensive and may not scale well with large datasets or frequent updates.

Utilizing AI techniques, such as natural language processing (NLP) and machine learning, provides an automated and efficient solution to clean and standardize data. AI algorithms can analyze and process data at scale, identify and correct errors, validate data integrity, and standardize formats and units.

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