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The Discovery of data is an iterative process, so it does not require a complete model to be constructed at the start of the analysis. Before data can be properly analyzed it must be prepared.
This requires someone with specific skills in handling and formatting data, often a data scientist. Data discovery may help analysts understand data patterns and trends through data visualization and advanced guided analytics.
The visualization methods are typically numerous, offering different ways for analysts to inspect data so that more patterns are seen.
While machine vision can be used to pick up on patterns as well, data discovery platforms often rely on the natural inclination of humans to find patterns visually.
Further delving into the meaning of the patterns is the stage of complex guided analysis. These functions enhance pattern-finding with machine learning capabilities and help analysts glean extra statistical information from data.
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