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Augmented Analytics refers to the use of machine learning (ML), artificial intelligence (AI), and natural language processing (NLP) to enhance data analytics by automating data preparation, insight generation, and explanation. Unlike traditional analytics methods that require specialized data science skills, augmented analytics simplifies the process, enabling business users and decision-makers to interact with data using conversational queries or visual dashboards. This democratization of data analysis allows organizations to identify patterns, trends, and anomalies more efficiently, fostering faster, more informed decision-making.
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