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Reusable Rule Repository

RightSight User Guide  ·  Module 4 of 14

Reusable Rule Repository v7.6 beta

Create, manage, import, and AI-generate reusable data quality rules that can be deployed across connections.

Overview

The Reusable Rule Repository is the centralized catalog of data quality rules that can be shared and deployed across multiple connection profiles. Rules defined here serve as templates — they are instantiated per-connection when the AI Rule Agent generates connection-specific rules.

Target Persona: Data Stewards, DQ Engineers, Data Governance leads.

Prerequisites: Business Terms should be defined (optional but rules can be linked to terms); RightSight license.

How This Module Helps

The Reusable Rule Repository is your rule template library. Instead of defining the same "not null" check for every connection, you define it once here and deploy it everywhere. This ensures: - Consistent DQ standards across all data sources - Centralized rule management — update a rule once, deploy everywhere - Rule lineage — track where each rule is deployed via the Where-Used panel - AI acceleration — the AI Rule Agent references these rules when generating connection-specific rules

Connects To Relationship
Business Terms Rules are linked to business terms
AI Rule Agent Agent uses repository rules as templates
Review & Confirm (DQ) Deployed rules appear for review
DQ Results Rule execution results
DQ Command Center Rule quality scores
Enterprise Trust Map Rule deployment coverage
Method Path
Sidebar Observability → RightSight → Reusable Rule Repository
URL /reusable-rule-repository
Wizard Augmented DQ Config → Step 3 (Rules)

Features & Workflows

1. Landing KPIs (RuleRepositoryKPIs)

KPI Description Click Action
Total Rules All rules in the repository Clears filters
Active Currently active rules Filters to active
Deprecated Rules marked as deprecated Filters to deprecated
AI-Generated Rules created via AI generation Filters by AI source
Deployed Rules deployed to at least one connection Filters to deployed
Rule Repository KPI cards
Figure 1: Rule Repository KPI cards

2. Creating a Rule

Steps

  1. Click + Create Rule in the toolbar.

  2. The Create Rule Modal opens.

  3. Fill in the rule definition:

Field Type Required Validation Description
Rule Name Text Yes Unique, max 200 chars Descriptive rule name
Description Textarea No Max 1000 chars Business context
Business Term Dropdown No Must be existing term Link to a business term
DQ Dimension Dropdown Yes — Completeness, Accuracy, Uniqueness, Validity, Timeliness, Consistency
Rule Type Dropdown Yes — Expression, Uniqueness, Schema Validation, Missing Data, Anomaly
Expression Code editor Conditional Valid SQL SQL expression (required for expression-type rules)
Severity Dropdown Yes — Critical, High, Medium, Low
Threshold Number No 0–100 Alert threshold percentage
  1. Click Save to create the rule.
What Happens Next
  • The rule appears in the Rules Table with status = Active.
  • The rule is available for deployment via the AI Rule Agent.
  • If linked to a business term, the rule appears in the term's Rules Sheet.
  • The KPI counts update.
Error Scenarios
  • Duplicate rule name — Validation error: "A rule with this name already exists."
  • Invalid SQL expression — Syntax highlighting shows errors; Save is disabled.
  • Missing required fields — Save button remains disabled.

3. Viewing Rule Details

Steps

  1. Click any rule row in the table.
Click rule row
Figure 2: Click rule row
  1. The Rule Detail Drawer opens with tabs:
Rule Detail Drawer
Figure 3: Rule Detail Drawer
Tab Description
Summary Rule details, metadata, and status
Edit History Audit trail of all changes
Validation Test the rule expression
Where Used All connections where this rule is deployed
  1. Click Where Used to see deployment across connections.

4. Editing a Rule

Steps

  1. Open the Rule Detail Drawer by clicking the rule row.

  2. Click Edit in the drawer header.

  3. Modify fields as needed.

  4. Click Save to apply changes.

What Happens Next
  • The change is recorded in the Edit History tab.
  • Deployed instances of this rule are not automatically updated — they retain their configuration at deployment time.

5. Deprecating a Rule

Steps

  1. Click the deprecate action on a rule row (via the context menu ⋮).

  2. The Deprecation Confirmation Dialog appears showing impact.

  3. Confirm → rule status changes to Deprecated.

What Happens Next
  • The rule remains visible in the repository but cannot be deployed to new connections.
  • Existing deployments are unaffected.
  • Use this instead of deletion to maintain audit trail.

6. Deleting a Rule

Steps

  1. Click the delete action on a rule row (via the context menu ⋮).

  2. The Delete Confirmation Dialog warns about impact.

  3. If the rule is deployed anywhere, the dialog shows the affected connections.

  4. Confirm → rule is permanently removed.

What Happens Next
  • The rule is removed from the repository.
  • Deployed instances remain in their connections but lose their repository link.

7. AI-Powered Rule Generation

Steps

  1. Click ✨ AI Generate in the toolbar.
AI Generate button
Figure 4: AI Generate button
  1. The AI Generate Rules Drawer opens with a 5-step wizard:
AI Generate Rules Drawer
Figure 5: AI Generate Rules Drawer
Step Title Description
1 Glossary Scope Define company name, industry, domain, and number of rules
2 Review Recommendation Preview AI-generated rules
3 Deduplication Review and resolve duplicates against existing rules
4 DQ Rules Review Review data quality rules per generated term
5 Generate Terms Complete the generation process

Step 1 — Glossary Scope:

AI Generate Step 1
Figure 6: AI Generate Step 1

Step 2 — Review Recommendation:

AI Generate Step 2
Figure 7: AI Generate Step 2

Step 3 — Deduplication:

AI Generate Step 3
Figure 8: AI Generate Step 3
  1. Complete all steps and click Generate.
AI Generate complete
Figure 9: AI Generate complete
What Happens Next
  • Generated rules are added to the repository with status = Active.
  • Each rule includes an AI-generated expression and severity.
  • Duplicates detected in Step 3 are skipped.

8. Import Rules

Steps

  1. Click ↑ Import in the toolbar.

  2. Download the CSV/Excel template.

  3. Fill in rules following the template format.

  4. Upload the completed file.

  5. Preview imported rules — duplicates are highlighted.

  6. Confirm import.

9. Export Rules

Steps

  1. Click ↓ Export in the toolbar.

  2. Select rules to export (or export all).

  3. Choose format (CSV, Excel).

  4. Download the file.

10. Bulk Upload Wizard

  1. Click Bulk ↑ in the toolbar.
  2. Upload a file with multiple rules.
  3. Step through validation and mapping.
  4. Confirm and create all rules at once.

11. Filters

Click the Filter button to open the Filters Sheet:

Filter Options
Status Active / Deprecated / All
DQ Dimension Completeness, Accuracy, Uniqueness, etc.
Rule Type Expression, Uniqueness, Schema, etc.
Business Term Any linked term
Source AI-Generated / Manual / Imported

12. Threshold & Notification Configuration

Each rule can have: - Threshold Configuration — Define acceptable thresholds (e.g., "fail if > 5% null values"). - Notification Configuration — Set up alert channels and recipients.

From Reusable Rules Navigate To
Rule → linked business term Business Terms
Rule → deployed to connections via AI Agent AI Rule Agent
Rule → reviewed in Review & Confirm Review & Confirm (DQ)
Rule → execution results DQ Results
Rule → quality scores in Command Center DQ Command Center
Rule → ETM Rule Deployment tab Enterprise Trust Map
Wizard → next step Metadata Extract & Enrich

Tips & Best Practices

  • Create rules at the business-term level for maximum reusability.
  • Use the AI generation wizard to quickly bootstrap domain-specific rules.
  • Regularly review the Where-Used panel to understand rule coverage.
  • Deprecate rather than delete rules to maintain audit trail.
  • Export rules before major changes for backup purposes.
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