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- Filtering a subset of records. For example, you can review patterns for a column of addresses and filter the rows of data where no street number is provided, based on patterns you select.
- Standardize values. You can make selections of patterns for the different patterns for phone numbers. See Pattern Matching by Data Type below.
- Extract values. You can break apart column values based on mismatches in structure. For example, apartment numbers from an address field can be extracted into a new column.
- Variable levels of abstraction. As demonstrated in the previous example, you may be able to select from multiple matching patterns to determine which one is the best fit for the row values of interest.
Machine Learning
Additionally,
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- See Explore Suggestions.
- See Suggestion Cards Panel.
- For more information on how the platform predicts suggestion cards based on selection, see Overview of Predictive Transformation.
Browse Pattern History
In fields in the Transform Builder that accept patterns, you can choose to review and select patterns from your recent history:
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In the Column Details panel, you can review sets of patterns that describe subsets of the values in the column. When you select one of the patterns, you are prompted with a set of suggested transform steps to apply to the data. See Column Details Panel.
Advanced Uses
In addition to the above basic uses, patterns can be used as the basis for the following advanced uses and more.
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