Defining a Data Quality Policy
Creating a Data Quality Policy
Data quality policies are guidelines that describe what criteria data must meet to be useful and reliable within an organization.
A data quality policy is part of a Policy framework. It describes:
• the objects to which it applies
• the dimensions that constitute the quality criteria to be respected
Example
A school policy requires parents of new students to complete a form that includes a medical questionnaire and emergency contact information, as well as confirmation of the student's name, address and date of birth.
A data quality policy is defined: it must respect the "Completeness" dimension, with a threshold whose value must be equal to 100%.
To create a data quality policy in HOPEX Data Governance:
1. Click the navigation menu then Compliance > Data Quality Policies.
2. In the edit area, click New.
3. Specify:
• the name of the data quality policy
• a description
• the subject, which represents the constrained asset
• the dimension

A dimension of data quality is a measurable characteristic of the data. For more details, see
Quality Dimensions.
4. Click OK.
The data quality policy appears in the edit area.
Defining Data Quality Controls
Implementation controls may be associated with the control directives.

Control directives are an interpretation of the law and contribute to the enforcement of any regulation article your organization has to comply with.
To create a data quality control:
1. Click the navigation menu then Compliance > Operational Assurance.
2. In the edit area click Data Controls.
3. Click New.
4. Enter the name and an owner if necessary.
5. Click OK.
The control appears in the edit area.
6. Hover the cursor over the control and click the
Properties 
button to define its characteristics:
• Code: enables unique identification of the control.
• Nature: corrective, detective, preventive
• Frequency: daily, weekly, monthly, at each transaction, bi-monthly
• Control directive associated with the control

Control directives are an interpretation of the law and contribute to the enforcement of any regulation article your organization has to comply with.
• Regulation articles of a the regulatory framework concerned
• Data Quality Measure

Data Quality Measure is what should be enforced to ensure the quality of Data.
• Execution Control
Identifying Data Quality Issues
When data quality controls are found to be unsatisfactory, you can specify quality issues and implement action plans to address them.
To define a data quality ssue:
1. Click the navigation menu then Compliance > Operational Assurance.
2. In the edit area, click the Data Issues tab.
The list of data issues appears.
3. Click New.
4. Name the issue and click OK.
The issue appears in the edit area.
Addressing the Data Quality Issues Encountered: Action Plans
You can set up action plans to improve a quality control that has been considered unsatisfactory.
To create an action plan:
1. Click the navigation menu then Compliance > Operational Assurance.
2. In the edit area, click the Action Plans tab.
The edit area displays:
• All action plans
• Delayed action plans
3. In the All Action Plans tab, click New.
4. Indicate the name of the action plan and possibly a comment as well as the start and end dates.
5. Click OK.
The action plan appears in the list.
6. Hover the cursor over the action plan and click the
Properties 
button to define its characteristics.
Properties of an action plan in HOPEX Data Governance
Main characteristics
You can specify the following information:
• Name: action plan name.
• Owner: this field is specified by default by the user who created the action plan.
• Owner Entity: entity responsible for action plan implementation.
• Approver: user responsible for validation of the action plan when all actions are completed.
• Means: text description of means required/desired for action plan execution.
• Priority: enables indication of a level. Priority can be:
• "Low"
• "Medium"
• "High"
• "Critical"
• Origin: enables definition of the context of carrying out the action plan:
• "Audit"
• "Compliance"
• "Event"
• "Risk"
• "RFC"
• "Other".
• Category: the action plan can for example be connected to:
• risk impact reduction
• project management
• process improvement
• control performance improvement
• etc.
• Other values are available.
• Nature: enables definition of whether the action plan is:
• Corrective
• Preventive
• Comment: supplements information on the action plan and its characteristics.
• Steering Calendar: used for sending reminders to the person responsible for an action plan so that they can indicate action plan progress.

A steering calendar for monthly reminder of progress is supplied by default.
• Action Plan Status : indicates at which stage of the workflow the action plan is located.
Financial assertion
• Forecast Cost: action plan cost estimate.
• Forecast Cost (Man-Days): estimate in man-days of action plan implementation workload.
Responsibilities
The user defined as action plan Responsible is responsible for definition of actions to be carried out and their execution.
This section is defined by the action plan creator or the action plan approver.
Success factors
In the Success Factors section, you can specify in text the success indicators enabling assessment of success of the action plan.
Scope?
To position an action plan in its environment, you can associate objects with the action plan in the Scope section.
You can connect objects of the following types:
• controls
• applications
• risks
• entities
• processes
• problems
Milestones
Milestones are key dates of the action plan.

The planned end date is mandatory.
Actions
The owner of the action plan must define actions enabling execution of the action plan. The owner can create actions and assign these.
7. In the Actions section, click New.
8. Fill in the columns associated with the action.
Attachments
You can attach business documents to an action plan:

For more details on the use of business documents, see the
HOPEX Common Features guide.