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Data storytelling is a powerful technique that helps analysts convey complex data insights in a way that is easy for non-technical stakeholders to understand. By structuring the presentation of data like a narrative, with a clear beginning, middle, and end, and using visualizations and relatable examples, analysts can help their audience connect with the data. This technique emphasizes clarity, context, and relevance, ensuring that the insights are not only understood but also actionable. The goal is to engage the audience emotionally and intellectually, making the data more accessible and persuasive. Option A (It allows the audience to ignore statistical significance) is incorrect because data storytelling still relies on presenting statistically valid information. Option C (It increases the amount of raw data presented) is incorrect as data storytelling focuses on simplifying and summarizing key insights, not overwhelming the audience with raw data. Option D (It removes the need for visualization) is incorrect because visualizations are often a key part of data storytelling, helping to illustrate the narrative. Option E (It focuses primarily on providing raw numbers) is incorrect because storytelling emphasizes insights and context over raw data.
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