Concept: Data Quality Module
The
Data Quality
module checks your field mapping configuration data to verify that the data satisfies the usefulness, completeness, and correctness requirements of People Analytics and Storyteller. The Data Quality
module checks these data for issues that will negatively impact your People Analytics installation and application and returns data quality defects that may need to be addressed before proceeding.Workday automatically runs the Data Quality module when you install or reinstall People Analytics, but you can also run it manually. Workday recommends that you manually run the
Data Quality
module before reinstalling People Analytics to check that any newly made configuration changes meet all requirements. You can run Data Quality from the Configure People Analytics
report and view the results by accessing the People Analytics Data Quality
report.Some defects have a greater negative impact than other defects. Workday assigns a severity level to each defect:
- Critical. Critical defects can prevent People Analytics from installing successfully. These defects can also severely impact the quality of data and the integrity of analysis results, and can potentially impact constrained security. If encountered, address the critical defects in theConfigure People Analyticsreport or in your underlying data.
- Major. Major defects won't prevent a successful installation, but they can severely impact the quality of data and the integrity of analysis results. Workday recommends that you address these issues in theConfigure People Analyticsreport.
- Moderate. Moderate defects can impact the quality of the KPIs, visualizations, and focus insights in People Analytics. You may ignore them as their impact on the quality of data is minimal.
The Data Quality module includes these check types:
Cardinality
Checks the number of unique values in a particular field. Compares the number to a threshold defined for that field, and checks whether the cardinality for the field is consistent in terms of expected levels within the hierarchy. Workday returns the field that fails the check and shows the cardinality of the field in the Value column.
High cardinality (a lot of unique values) can negatively affect Storyteller engine performance, and it might also result in low quality focus insights due to a large number of smaller populations.
Cross Pipeline
Consistent Values
Checks the consistency of values across pipelines and compares the two pipeline-to-pipeline values to a defined threshold. Currently, the threshold is when no values overlap in the same field in each pipeline.
Workday returns the fields from each pipeline that fail the check and shows the percentage of inconsistent values from each pipeline in the Value column.
Data Types
Checks whether a particular field in multiple pipelines is the same by inspecting the field type. Workday returns the field that fails the check and shows the data types for the field in the Value column.
Cross pipeline defects can severely impact filtering on the KPIs tab by preventing a population filter you configure from filtering data in multiple pipelines.
Duplicates
Checks whether there are multiple records of the same worker. Workday returns the Employee ID or Candidate ID and shows the number of multiple records in the Value column.
Duplicate records cause inaccurate headcounts, potentially with exponential impact.
Illogical Values
Checks if a particular field contains values that fail logic rules defined for that field. Example: if the hire date is in the future. Workday returns the field that fails the check and shows the percent of illogical values for that field in the Value column.
Illogical values can lead to inaccurate metrics in topics, leading to inaccurate data in visualizations, KPIs, and focus insights.
Invalid Values
Checks if a particular field contains values that aren’t in the list of valid values defined for that field. Workday returns the field that fails the check and shows the percent of invalid values for that field in the Value column.
Invalid values can lead to inaccurate metrics in topics, leading to inaccurate data in visualizations, KPIs, and focus insights.
Missing Values
Checks how many values a particular field is missing. Missing values can be blank or NULL. Workday returns the field with missing values and shows the percent of missing values for that field in the Value column.
Missing values might skew the data presented in People Analytics, preventing an accurate reflection of your workforce.
Multiple Hierarchies
Checks whether a child in a hierarchy has parents across multiple hierarchies. Workday returns the field of the child hierarchy with parents across multiple hierarchies and shows the number of multiple hierarchies in the Value column.
A multiple hierarchies defect can result in inaccurate data due to duplication, and it can negatively impact constrained security by potentially displaying to a viewer workers who aren’t in their organization.
Population
Checks the number of unique values in a particular VIBE Index intersection, and compares the number to the minimum headcount requirement defined for VIBE Index intersections. Workday returns the intersection field and the number of intersections that fail the check, and shows the number of records for intersections that don’t have sufficient populations in the Value column.
Population check defects cause Workday to exclude a particular intersection from the VIBE calculation.
Skill Category Cardinality
Checks whether you use fewer than 10 distinct skill category values (from Skills Cloud only). Workday returns the current number of skill category values. A low number of skill categories can lead to limited data granularity and unusable results.
Access the
Maintain Skill Item Categories
task and update your skill category catalog.Uncategorized Skills Rate
Checks whether the percentage of skills not assigned to any skill category exceeds a threshold of 5%. If it does, Workday returns the percentage of skill values that fail the check. Use the
Maintain Skill Item Categories
task to categorize the highlighted skills.A high number of uncategorized skills can lead to limited data granularity and unusable results.
Match Score Availability Distribution
Match score is a calculation that compares workers' current portfolio of explicit or inferred skills to the skills listed on their job profile. This Data Quality check verifies whether workers in your population are assigned a match score. Workday returns a donut chart viz of your worker population divided into groups based on the match score availability. Workers with no match score are split depending on the reason:
- No skills filled or to be inferred from the worker’s profile.
- No skills filled or to be inferred from the worker’s job position.
- Skills for the job position don’t match the skills in Skills Cloud.
High numbers of workers without a match score might skew the data presented in People Analytics, preventing an accurate reflection of skills present among your workforce.
Click any segment of the chart to view: the worker and corresponding job profile, employee ID, and reason for no match score. You can export the table to a Workday Discovery Board.