For a list of common tasks to cleanse your data, see Cleanse Tasks.
Assess Data Quality
You can create data quality rules to apply to the specifics of your dataset. For example, if your dataset includes square footage for commercial rental properties, you can create a data quality rule that tests the
sqFt field for values that are less than 0. These values are flagged in red in a data quality bar for the rule for easy review and triage.
Tip: Data quality rules are not transformation steps. They can be used to assess the current state of the data and are helpful to reference as you build your transformation steps to clean up the data.
For more information, see Overview of Data Quality.
After you have performed initial cleansing of your data, you might need to perform modifications to the data to properly format it for the target system, specify the appropriate level of aggregation, or perform some other modification.