¶ Basic Information
| Key | Value |
|---|---|
| Table | DS16 Risk Register Tasks |
| Severity | MINOR |
| Unique ID | 1160566 |
| Summary | Are the likely impact days for schedule greater than the max impact days? |
| Error message | impact_schedule_likely_days > impact_schedule_max_days. |
¶ What causes this error?
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The Data Integrity and Quality (DIQ) check titled "Likely Impact Schedule Days Greater Than Max Days" is performed on the DS16 Risk Register Tasks table. This check is designed to ensure that the likely impact days for a schedule do not exceed the maximum impact days.
If an error is flagged by this DIQ check, it indicates that the value in the 'impact_schedule_likely_days' field is greater than the value in the 'impact_schedule_max_days' field. This is inconsistent as the likely impact days should not exceed the maximum impact days.
To resolve this issue, review the data entered in these fields. The 'impact_schedule_likely_days' should be a value less than or equal to the 'impact_schedule_max_days'. If the likely impact days are greater, it suggests an error in data entry or calculation. Correcting the values to ensure the likely impact days do not exceed the maximum impact days will resolve this error.
¶ Why do we check this?
This test is being performed on the 'DS16 Risk Register Tasks' table to ensure that the 'likely impact days for schedule' are not exceeding the 'max impact days'. The test is checking if the value of 'impact_schedule_likely_days' is greater than 'impact_schedule_max_days'.
The importance of this check is to maintain the integrity and accuracy of the project schedule data. If the likely impact days are greater than the maximum impact days, it could indicate a potential error in data entry or a miscalculation in the project schedule. This could lead to incorrect risk assessments and misinformed decision-making.
The severity of this test is marked as an 'MINOR', which means it is not a critical error that would prevent the data from being reviewed, but it is a potential issue that could cause minor problems or indicate that the data does not adhere to best practices. It is advisable to address this issue to ensure the accuracy and reliability of the project management data.
¶ Code
CREATE FUNCTION [dbo].[fnDIQ_DS16_RR_Tasks_IsImptSchedLikelyGtMax] (
@upload_id int = 0
)
RETURNS TABLE
AS RETURN
(
SELECT
*
FROM
DS16_risk_register_tasks
WHERE
upload_ID = @upload_ID
AND impact_schedule_likely_days > impact_schedule_max_days
)