How the data flow UI works
To help you navigate your data flow, Data Wrangler has the following tabs in the top navigation pane:
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Data flow – This tab provides you with a visual view of your data flow step where you can add or remove transforms, and export data.
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Data – This tab gives you a preview of your data so that you can check the results of your transforms. You can also see an ordered list of your data flow steps and edit or reorder the steps.
Note
In this tab, you can only preview data visualizations (such as the distribution of values per column) for Amazon S3 data sources. Visualizations for other data sources, such as Amazon Athena, aren't supported.
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Analyses – In this tab, you can see separate sub-tabs for each analysis you create. For example, if you create a histogram and a Data Quality and Insights (DQI) report, Canvas creates a tab for each.
When you import a dataset, the original dataset appears on the data flow and is named Source. SageMaker Canvas automatically infers the types of each column in your dataset and creates a new dataframe named Data types. You can select this frame to update the inferred data types.
The datasets, transformations, and analyses that you use in the data flow are represented as steps. Each time you add a transform step, you create a new dataframe. When multiple transform steps (other than Join or Concatenate) are added to the same dataset, they are stacked.
Under the Combine data option, Join and Concatenate create standalone steps that contain the new joined or concatenated dataset.
