Integrating Informatica Data Quality IDQ with Informatica MDM

Integrating Informatica Data Quality (IDQ) with Informatica Master Data Management (MDM) is a critical step for organizations striving to maintain high data quality and consistency across their master data management workflows. This comprehensive guide offers a step-by-step approach to achieve this integration effectively.

Understand the Architecture

Informatica MDM is designed to manage master data across an organization, ensuring its accuracy and consistency. On the other hand, Informatica IDQ focuses on assessing and improving the quality of data, ensuring that the data entering MDM is clean and reliable. This integration ensures that your data quality processes are in harmony with your MDM workflows.

Setup Prerequisites

To ensure a successful integration, it is essential to have both Informatica MDM and IDQ properly installed and configured in your environment. Additionally, verify that you have the necessary licenses for both products. This setup ensures that you have the tools and permissions required to facilitate the integration effectively.

Data Quality Processes in IDQ

Define Data Quality Rules

The first step in the IDQ process is to create Data Quality Rules. These rules help in validating, cleansing, and standardizing the data. Validate for duplicates, format validation, and enrichment to ensure that the incoming data meets your quality standards.

Create a Data Quality Mapping

Using the IDQ Designer, create mappings that will apply these rules to your data sources. This allows for a systematic approach to cleaning and normalizing the data, making it ready for MDM processes.

Integration with MDM

Use IDQ as a Pre-Processing Step

Before data is loaded into MDM, use IDQ to process and cleanse the data. This is typically done during the ETL (Extract, Transform, Load) phase. This ensures that the data is as clean and reliable as possible before it reaches MDM.

Configure IDQ in MDM

In MDM, configure the integration to call IDQ processes. This can be done by setting up a data quality task within the MDM workflow. This step ensures that MDM leverages the data quality resources provided by IDQ, enhancing the overall quality of the data stored in MDM.

Leverage IDQ Web Services

Utilize the IDQ web services to invoke data quality processes from MDM. This allows for real-time validation and cleansing of data as it is being processed, ensuring that data issues are addressed immediately.

Data Synchronization

Once the data has been processed by IDQ, ensure that it is properly synchronized with MDM. This may involve setting up job schedules or triggers that manage when data is sent between the two systems. Effective data synchronization ensures that the data in MDM reflects the changes made during the IDQ process.

Monitoring and Reporting

Monitor Data Quality

Use IDQ’s monitoring tools to track the effectiveness of your data quality rules. Regular monitoring helps in identifying any issues and ensures that the data being managed by MDM is of high quality and meets the defined standards.

Create Reports in IDQ

Create reports in IDQ to visualize data quality metrics and share these insights with stakeholders. Reports can include key performance indicators (KPIs) such as data accuracy, completeness, and consistency, helping stakeholders understand the current state of data quality.

Testing

Conduct thorough testing to ensure that the integration works as expected. Validate that the data entering MDM is of high quality and meets the defined standards. Testing is crucial in identifying any potential issues before the integration goes into production.

Documentation and Training

Document the integration process and provide training for users on how to maintain and monitor data quality within the MDM framework. Documentation helps in ensuring that users understand the integration process and can troubleshoot any issues that may arise.

Example Use Case

Scenario

A retail company needs to ensure that customer data entering its MDM system is free of duplicates and formatted correctly.

Process

Data is extracted from various sources. IDQ processes the data using defined rules to identify duplicates and standardize formats. Cleansed data is then loaded into the MDM hub. MDM uses this high-quality data for further operations.

This example illustrates how the integration of IDQ with MDM ensures that data is cleaned and standardized before it reaches MDM, improving the overall quality and accuracy of the data.

By following these steps, you can effectively integrate Informatica Data Quality with Informatica MDM, ensuring that your organization’s master data is both accurate and reliable.