A company wants to analyze thousands of live-chat transcripts to discover customer sentiment and common topics. Compared with traditional business intelligence tools, which business value of machine learning best meets this need?
It primarily lowers storage costs by moving data to archive tiers.
It can automatically extract insights from unstructured text data at scale.
It eliminates the need for visual dashboards by producing static monthly reports.
It guarantees 100% prediction accuracy without human intervention.
Machine learning models trained on natural-language data can automatically detect sentiment, classify topics, and recognize entities in large collections of text. This unlocks insights from unstructured data at a scale that manual rules or standard BI reporting cannot match. Lowering storage costs, guaranteeing perfect accuracy, or replacing dashboards with static reports are not core advantages of ML-and none of these by themselves would address the challenge of extracting meaning from free-form chat transcripts.
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