Data Validation ensures that the data captured from your agent have undergone data cleansing to ensure that the data is both correct and useful. Sequentum Enterprise makes data validation simple and easy through a centralized screen where every field can be configured to ensure quality.
Click on the Data tab and then click on Validation Rules under Data Validation.
Data Validation Screen.
Sequentum Enterprise supports the following data types for captured data.
|Short Text||All content will be captured as Short Text by default. Short Text content can be up to 4000 characters long.|
|Long Text||Long Text content can be any length, but cannot always be used in comparisons, so you may not be able to include Long Text content in duplicate checks.|
|Integer||A whole number.|
|Float||A floating point number.|
|Date/Time||A date and/or time value.|
A value that can be true or false. Boolean values are stored as 1 or 0 integer values.
Specifies whether the captured column can be empty or not.
Data captured can be formatted into the following styles:
- Regular Expressions
- Numeric Value Range
Script to format the captured data into the formatted style.
If a captured data is defined as a date/time, a time zone can be used to determine what time zone the data was collected in. The following are selections for time zone:
- Assume Local Time
- Assume Universal Time
- Adjust to Universal Time
Data validation can be applied to the agent at different time, be default, the agent is configured to execute data validation during runtime while the agent is collecting data. This can be changed to export so that the data validation is applied when the agent is finished running and executing the export script.
Export and Runtime Validation
There are different validation error handling options that can be applied to the agent.
- None - Do nothing when there is a data validation error.
- Remove Row - Removes the row from the export data.
- Remove Row and Increase Error - Removes the row from the export data and also increase the error count.
- Trigger Failure - Triggers a failure and the agent will fail.
System values are not stored in the internal database.
A key column is used to uniquely identify a data entry. Multiple capture commands can be marked as key columns to combine extracted data from multiple commands into a value that uniquely identifies a data entry.
Export Validation is executed during data export. It is possible to manipulate empty tables, empty rows, and handle duplicate rows.
Empty table handling:
Specifies what happens when there is an empty table:
- Remove Table and Trigger Error
- Trigger Export Failure
Empty row handling:
Specifies what happens when there is an empty row:
- Remove Row and Trigger Error
- Trigger Export Failure
Duplicate row handling:
Specifies what happens when there is a duplicate row:
Note: If there is a Key column defined, the key will be used to determine a duplicate row, otherwise if there is no Key defined, the hash value (SHA 512) of the entire row is used to determine a duplicate.
- Remove (SHA-512)
- Remove (Key Values)
- Remove (Key Values Across Sessions)