Data Quality Studio

Autor: To-Increase B.V.

Enable a data-driven business strategy without development efforts, using a data quality solution

Data Quality Studio (DQS) from To-Increase is a solution to configure data quality policies for data validation, enrichment, and cleansing without the need for development. DQS helps organizations achieve high data quality within Microsoft Dynamics 365 Finance & Operations. The solution is a unique offering that ensures valid, accurate, complete, and consistent data at the time of need. There is no additional development effort required to set up this premium data governance tool, supporting organizations focusing on a data-driven business strategy. DQS ensures consistent and reliable data delivery to all your stakeholders for improved operational effectiveness and customer satisfaction. DQS can be used as a stand-alone component, but it can also work well with other To-Increase solutions such as Master Data Management (MDM) and Data Modeling Studio (DMS). DQS is a solution designed to make data quality the cornerstone of your data-driven business strategy. The solution ensures high-quality master data and transactions, improves reliability in reporting, and reduces data entry errors. DQS enhances business value by setting up data validations, and by eliminating duplicate data through automation, it creates a single source of truth.

The main features of DQS are:

1. Data Cleansing and Enrichment- You can configure data actions to autocomplete fields with specific values. These values can be conditional, i.e., they can differ according to your business requirements.

2. Duplicate Checks- Duplicate data leads to inaccurate reporting and less informed decisions. You can set up comparison rules on data to prevent the entry of duplicate records.

3. Periodic Governance Checks- You can set periodic consistency checks to identify records that do not meet the validation rules.

4. Data Quality Policies- DQS allows you to create additional validation or enrichment rules at the field or record level to ensure users enter the correct values. These rules can be set conditionally for specific legal entities or based on the value/content in fields or tables. It offers you an easy way to enforce data validation, thereby improving data quality.

5. Data Patterns- The data validation rules set up using DQS can have data patterns to enforce the correct formatting of the data entered.

6. Web Services- You can check for valid data entry or data enrichment by integrating DQS with your own or third-party web services.

7. Enhanced User Interaction- DQS enables the monitoring of data entry by users, according to the data quality policies. In case of an error, the user is guided through clear messages and can focus on correcting it.

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