Foundational DQ - Blanks Rule

In this Article

• Introduction
• How to Configure the Rule
  • Step 1: Access Data Quality Rules
  • Step 2: Create a New Rule
  • Step 3: Define the Rule Parameters
  • Step 4: Save & Run the Rule

Introduction

The "BLANKS" rule addresses the availability and completeness of data within a dataset. It focuses on identifying whether there are any missing values present. This rule is particularly important for ensuring data integrity and accuracy.

For example, let's consider a dataset containing customer information, including ship-to addresses. The BLANKS rule might be applied to check if there are any records where the address field is empty or missing in the customer ship-to information. By enforcing this rule, one can ensure that all necessary data fields are populated, thus maintaining the quality and reliability of the dataset.

For further information about the rule detail page including scope, threshold, notifications, etc., please see the detailed article Rule Detail page.

How to Configure the Rule

Step 1: Access Data Quality Ruless

• Log in to DvSum and 
  • Navigate to Dictionaries → Database Tables.
  • Select the relevant Data Source and Table Name.
  • Data Quality → Choose Available Rules.

Step 2: Create a New Rule

• • Click "⊕ Add Rule".
  • Select the "Foundational DQ" category.
  • Choose "BLANKS".

 

Step 3: Define the Rule Parameters

• Select the Table and Column where blank values should be restricted.
• Fill in the Rule Description, and Column name.

If user selects:

• Treat Empty Strings as Blanks: Any field that contains an empty string ("") will be considered as a blank value.
• Treat Null Values as Blanks: Database-level NULL values will be treated the same as blank/missing values.

Note: To know more about the Null and Empty values for Blank Rule, refer the article Null and Empty Values.

Step 4: Save & Run the Rule

• Click "Save Rule".
• Click "Run" to execute and test the rule.