# Uniqueness Rules

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#### Uniqueness Rules

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.
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To access your catalog, please follow these steps:

1. Open **Google Chrome** web browser.
2. Navigate to:

{% embed url="<https://pdc.pentaho.lab>" %}

3. Enter following email and password, then click **Sign In**.

Username: <david.park@adventureworks.com> (mapped to Business Steward role)

Password: Welcome123!

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{% tab title="Duplicate Customer Detection" %}
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#### Duplicate Customer Detection

**Scenario:** Identify potential duplicate customer records based on name and contact info.
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**Business Rule Configuration:**

```
Rule Name: Customer_Duplicate_Detection
Description: Identifies potential duplicate customer records
Data Quality Dimension: Uniqueness
Schedule: Weekly
Target: Person.Person
```

**SQL Query:**

```sql
WITH DuplicateCandidates AS (
    SELECT 
        FirstName, 
        LastName, 
        EmailAddress,
        COUNT(*) AS DupCount
    FROM Person.Person p
    JOIN Person.EmailAddress e ON p.BusinessEntityID = e.BusinessEntityID
    GROUP BY FirstName, LastName, EmailAddress
    HAVING COUNT(*) > 1
)
SELECT 
    (SELECT COUNT(DISTINCT BusinessEntityID) FROM Person.Person) AS total_count,
    (SELECT COUNT(DISTINCT BusinessEntityID) FROM Person.Person) - 
        (SELECT SUM(DupCount - 1) FROM DuplicateCandidates) AS scopeCount,
    (SELECT SUM(DupCount - 1) FROM DuplicateCandidates) AS nonCompliant
```

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{% endtab %}

{% tab title="Unique Product Numbers" %}
{% hint style="info" %}

#### Incomplete Product Information

**Scenario:** Ensure ProductNumber is truly unique across all products.
{% endhint %}

**Business Rule Configuration:**

```
Rule Name: Product_Number_Uniqueness
Description: Validates ProductNumber uniqueness constraint
Data Quality Dimension: Uniqueness
Schedule: Daily
Target: Production.Product
```

**SQL Query:**

```sql
WITH DuplicateProducts AS (
    SELECT ProductNumber, COUNT(*) AS CountDuplicates
    FROM Production.Product
    GROUP BY ProductNumber
    HAVING COUNT(*) > 1
)
SELECT 
    COUNT(*) AS total_count,
    COUNT(*) - COALESCE((SELECT SUM(CountDuplicates - 1) FROM DuplicateProducts), 0) AS scopeCount,
    COALESCE((SELECT SUM(CountDuplicates - 1) FROM DuplicateProducts), 0) AS nonCompliant
FROM Production.Product
```

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---

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