Rule Groups

Rule Groups

In this series of detailed workshops we're going to:

• Understand the business value and ROI of implementing business rules

• Master the 7 Data Quality Dimensions in PDC

• Create and configure business rules with detailed step-by-step guidance

• Implement rule actions (Status, Tags, Webhooks) and understand their purpose

• Organize rules using rule groups for operational efficiency

• Monitor and interpret rule execution results for continuous improvement

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Accessing your Catalog

To get started using the Data Catalog, log in using the address and credentials provided by your Data Catalog service user or administrator.

To access your catalog, please follow these steps:

1. Open Google Chrome web browser.

2. Navigate to:

https://pdc.pentaho.labpdc.pentaho.lab

1. Enter following email and password, then click Sign In.

Username: [email protected] (mapped to Business Steward role)

Password: Welcome123!

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Daily Sales Quality Checks

Daily Sales Quality Checks

Scenario: Monitor that orders are being processed within expected timeframes.

Rule Group: Daily_Sales_Quality_Checks

• Customer_Email_Completeness

• Order_Date_Validity

• Order_SubTotal_Calculation_Accuracy

• Order_Processing_Timeliness

Configuration:

Group Name: Daily_Sales_Quality_Checks
Description: Critical daily validations for sales data integrity
Schedule: Daily at 6:00 AM
Rules: [4 rules listed above]

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Customer Overall DQ Score

Cutomer Overall DQ Score

Scenario: Comprehensive Customer Data Quality Score

Business Rule Configuration:

Rule Name: Customer_Overall_DQ_Score
Description: Composite data quality assessment across customer data
Data Quality Dimension: Accuracy
Schedule: Daily
Target: Person.Person, Sales.Customer

SQL Query:

WITH CustomerQuality AS (
    SELECT 
        c.CustomerID,
        CASE WHEN e.EmailAddress IS NOT NULL THEN 1 ELSE 0 END AS HasEmail,
        CASE WHEN pp.PhoneNumber IS NOT NULL THEN 1 ELSE 0 END AS HasPhone,
        CASE WHEN ba.AddressID IS NOT NULL THEN 1 ELSE 0 END AS HasAddress,
        CASE WHEN so.SalesOrderID IS NOT NULL THEN 1 ELSE 0 END AS HasOrders
    FROM Sales.Customer c
    LEFT JOIN Person.Person p ON c.PersonID = p.BusinessEntityID
    LEFT JOIN Person.EmailAddress e ON p.BusinessEntityID = e.BusinessEntityID
    LEFT JOIN Person.PersonPhone pp ON p.BusinessEntityID = pp.BusinessEntityID
    LEFT JOIN Person.BusinessEntityAddress ba ON p.BusinessEntityID = ba.BusinessEntityID
    LEFT JOIN Sales.SalesOrderHeader so ON c.CustomerID = so.CustomerID
),
QualityScore AS (
    SELECT 
        CustomerID,
        (HasEmail + HasPhone + HasAddress + HasOrders) AS Score
    FROM CustomerQuality
)
SELECT 
    COUNT(*) AS total_count,
    SUM(CASE WHEN Score >= 3 THEN 1 ELSE 0 END) AS scopeCount,
    SUM(CASE WHEN Score < 3 THEN 1 ELSE 0 END) AS nonCompliant
FROM QualityScore

Rule Actions with Multiple Thresholds:

• PASS: ≥ 95% customers with score ≥3 → Tags: "gold_standard"

• WARNING: 85-95% → Tags: "needs_improvement", Webhook to Data Steward

• FAIL: < 85% → Tags: "critical_remediation", Webhook to VP of Data

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First Tab

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Second Tab

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