Validating Project Data

Use the data validation function to filter out invalid data.

1. On the toolbar, click Validate.
2. Next to Data types and constraints, click Auto suggest.
3. In the "Configure data type" dialog, keep the default settings, click Next.
4. On the "Data type result" page, use the data types suggested by TIBCO Clarity, click Next.
5. Configure the constraints for the PATNO column data type:
   1. Change the data type from Integer to String.
   2. In the string/regular expression field, enter the regular expression:^\d\d\d$.
   3. Next to the Allows null check box, click Save to save the data type.
   4. In the "Save as data type" dialog, enter a name for the new custom type, and then click Add.
6. Define custom data types for each column as shown in the following table:

   Column Name	Description	Variable Type	Constraint	Clarity Constraint	Null Allowed?
   PATNO	Patient number	String	Numerals	Whole: ^\d\d\d$	Yes
   GENDER	Gender	String	’M’ or ’F’	Valid values: M, F	Yes
   VISIT	Date of visit	Date	Like 12/31/2013	MM/dd/yyyy	Yes
   HR	Heart rate	Integer	40 to 120	40 to 120	Yes
   SBP	Systolic blood pressure	Integer	80 to 200	80 to 200	Yes
   DBP	Diastolic blood pressure	Integer	60 to 120	60 to 120	Yes
   DX	Diagnosis code	String	1 to 3 digits	Length: 3	Yes
   AE	Adverse event	Boolean	None	None	Yes

   See the following figure for validation rules configured for each column:

   

7. Click Save changes to start validating data.

Result

The validating results are displayed on the data page. The rows that contain invalid values are marked with the icon. Click an icon to view the details.