Firstlogic® DQM for Informatica PowerCenter®

Firstlogic DQM for Informatica PowerCenter provides data cleansing, data matching and consolidation for data integration and migration projects.

Ensure Data Quality for Informatica PowerCenter

During data migration projects, having a strategy to assure the integrity of your data set is vital. Problems with data quality, such as inconsistent definitions and semantics, silos of information, and a lack of transparency can significantly slow or delay data migration projects. 


Data Quality Management for Informatica PowerCenter

Data Quality Management (DQM) for Informatica PowerCenter lets you embed and quickly deploy data quality functionality within the Informatica PowerCenter data integration process – so you can gain the highest level of reliability and accuracy.

With Firstlogic® DQM for Informatica PowerCenter, you can take advantage of the following features:

    • Prepackaged native integration – Leverage prepackaged data quality best practices and functionality for Informatica PowerCenter environments.
    • Data cleansing – Handle both structured and unstructured data formats, and prepare the information for matching through parsing and standardization.
    • Data matching and consolidation – Import entire files, set match criteria, split files into smaller groups for faster matching, and eliminate duplicates.
    • Global data cleansing and matching – Address global needs with functionality specific to locale and language.
    • Enforcement of your organization's specific business rules – Help ensure the information that enters your data warehouse or data store is the best fit for your organization.


Integrated Data Quality for Informatica PowerCenter

Firstlogic® DQM for Informatica PowerCenter can help you reap significant benefits:

    • Deliver high-quality – data with efficient, well-prepared data migration projects.
    • Eliminate duplicate and inaccurate information – reducing business disruption caused by poor-quality data.
    • Support core business processes and users – based on a foundation of trusted, quality data.
    • Improve project management – and efficiency with greater visibility and process transparency.
    • Identify early detection – of potential problems in data migration projects.
    • Achieve long-term data quality – with data governance processes that live on after the initial project.