![]() This is also useful for creating dashboards and reports that non-data-savvy decision-makers can understand. To make sense of all this information, we often represent it visually to aid our natural pattern-spotting abilities. Working with big data means grappling with thousands, if not millions, of discrete data points. But what visualization tools can we use to help? Let’s take a look. Interpreting datasets often involves representing them visually.
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