Data Quality - Customer policy

  • Published on Mar 20, 2026
  • 2 minute(s) read
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Introduction

High-quality data in your ERP system is essential. Accurate data benefits your organization in several ways:

  • Reduces troubleshooting, resulting in smoother daily operations.

  • Enhances decision-making by providing reliable insights.

  • Strengthens AI-driven analysis through complete and trustworthy data.

To maintain data quality, users must follow guidance during data entry in D365 F&SCM and conduct regular reviews of existing records. To support this process, STAEDEAN developed Data Quality Studio. This product helps validate and improve customer data quality.

For more information on Data Quality Studio, refer to the Data Quality Studio documentation. Note that each Data Quality Studio page has a button that refers to the related documentation topics.

To get a quick insight in how to set up Data Quality Studio, you can use the free 'Customer policy'. This is an example of a data quality policy that demonstrates how to use Data Quality Studio to check customer data.

Customer policy

The 'Customer policy' checks the quality of customer data stored in the CustTable table and LogisticsElectronicAddress table.

The 'Customer policy' has two key functions:

  • Assessment of existing customer data

    The policy identifies and reports records that do not meet data quality rules. You can then update these records accordingly.

  • Enforcement of data quality policies

    The policy ensures that newly created customer records comply with the data quality rules. When entered data does not meet the data quality rules, messages are shown.

The 'Customer policy' checks for the following data quality aspects:

Field

Rule type

Check type

Goal

  • Customer account

  • Customer group

  • Customer Classification group

  • Statistics group

  • Segment

  • Subsegment

  • Tax exempt number

  • Invoice account

  • Mode of delivery

  • Sales tax group

  • Currency

  • Credit limit

Validation rule

Mandatory

Ensure that all required and mandatory fields have a value. Minimize incomplete data.

Credit limit

Validation rule

Range expression

Ensure that values are within a certain defined range. Values outside the range are not accepted by the policy.

Sales order pool

Validation rule

Blank

Ensure that no values are entered in this field.

Credit rating

Validation rule

Configurable lookup

Ensure that a data entry user only can select values from a list of predefined values.

Contact number/address

Validation rule

Data pattern

Ensure that entered phone numbers are in the correct format and follow a certain pattern. In this example, a phone number must always start with a + symbol. Other patterns are not accepted.

Customer name

Duplicate check rule

Fuzzy matching

Ensure that only one customer account exists for each customer name.

Note

  • The 'Customer policy' is based on common fields used in D365 F&SCM. Some fields or data quality checks may not be relevant to your organization. Before you use the 'Customer policy', review the included fields and data quality checks. You can make changes to the 'Customer policy' to match your specific needs.

  • If you have several legal entities and the setup is identical across these legal entities, you can run the assessment across them.