When a validation rule is executed, it can have either of the following statuses:
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Icon |
Status |
Definition |
Example |
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Pass |
Audit rule is passing. If it is master data exception, there are 0 exceptions. If it is not of type master data, then the rule is meeting the criteria |
Forecast Name is 100% unique in SALES_FORECAST extract |
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Fail |
Audit rule is not of type master data and the rule is failing |
Run over run variance of qtyplanned in PURCHASE_PLAN is 5% for Supplier X which is more than the limit of 3% |
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Exception |
Audit rule is of type master data and there are 1 or more exceptions |
There are 2 routing records where yield is not between 0 and 1 |
Run Status & Readiness Score
Along with a status, a Readiness Score is also generated. Readiness score provides a second degree of information on the quality of data. If the data rule is failing, how bad is it. Readiness score creates a common unit for measuring the quality of data and allows result of audits calculating the overall data quality score across various data elements and types of audits.
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Sample Audit Result |
Audit Result Icon |
Readiness Score |
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Count of finish good items in item master is 6000 which is within the tolerance of 5500 and 7000 |
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100% |
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Count of finish good items in item master is 5000 which is not within the tolerance of 5500 and 7000 |
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91% (5000 is 9% short of 5500) |
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Count of finished good items in item master is 3000 which is not within the tolerance of 5500 and 7000 |
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54% (3000 is 46% short of 5500). Same test as above, but data quality is lower. |
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Forecast Name is 100% unique in SALES_FORECAST extract |
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100% |
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Run over run variance of qtyplanned in PURCHASE_PLAN is 5% for Supplier X which is more than the limit of 3% |
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33% (2% over limit of 3%) |
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There are 2 routing records where yield is not between 0 and 1. (total records are 100) |
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98% (98 out of 100 are good) |
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Following insights are available with your audit results
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Icon |
Insight Type |
Definition |
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History |
History for all audits |
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Exception List |
List of Exceptions for master data audits |
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Drill-down Analytical |
Drill-down with Variance for aggregation audits |
History Trend Insights
With history, you can get insights into the changes to the audit result from last run and also the trend of that audit over time. History insights can be useful to identify what audits to focus on.
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History Trend |
Definition |
Focus Required |
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Flat. No change |
Status Quo |
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Positive Up – Test was a fail before and now pass. Test has been failing because results too low but now trending up. Positive Down – Test has been failing because results were too high and now trending down. |
Things are improving even if the tests are failing. May not need to focus. |
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Negative Down – Test was passing before and is now failing. Or it has been passing but values are trending down and will cross the lower tolerance soon. Or it has been failing and things are getting worse Negative Up – Test was passing before and is not failing. Or it has been passing but values are trending up to cross the upper tolerance soon |
Things are getting worse for failed tests – requires top priority focus. Things are trending in the wrong direction for passing tests – heads-up for future issues |
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