Implement PartyQualityInsight™

DataQualityFirst partners with regional and global systems integration firms as well as IBM software services to implement PartyQualityInsight™ with IBM InfoSphere™ DataStage® and QualityStage®. Most customers and all partners utilize formal methodologies to design, develop, test and implement data integration solutions. The components and process outlined below are aligned with the preferred methodology. There are six major components in a plan to implement PartyQualityInsight™:

1. Source data – specifics of the party data sets to be processed with PQI.
2. IBM Information Server environment – details of the current and planned configuration.
3. Implementation pattern – description of how PQI with DataStage® and QualityStage® is deployed, customized and integrated in the to be architecture. The four basic implementation patterns are:
   1. Load and Maintain – Process, de-duplicate and integrate one or more party data sources to identify duplicates and relationships between parties and load a variety of targets. Support customer master files, improve and maintain the quality of the party dimension in the warehouse, clean up the data in the CRM system, load the new ERP application and improve the enrichment process for external data.
   2. Reference Match – Process a single source against a master file to determine if the parties on the source data set are or are not on the master file.
   3. Real time validation – Process a single transaction to determine that the party represented on the transaction is or is not on the master file. Standardize party data attributes and link party records by invoking PQI processes deployed as services from the application, in the database or in the messaging environment. Party data quality logic is available as "always on" data services in a loosely coupled architecture.
   4. Customer data governance – Actively manage the business definition, logic and quality of party data in a variety of implementation scenarios as part of a formal governance program.
4. PQI Package customization - One important note about developing high quality data integration applications is that it is always an iterative process. That is because every organization’s data is different, just as the business rules to process, match and format the data are specific to a particular project implementation. As a pre-packaged application for party data, PQI will generate an initial baseline very quickly. From there business subject matter experts and technical personnel evaluate the data and confirm business requirements and rules. Updates are often made in the source system as well as to the rules for standardization and matching. Then PQI runs again against a party dataset and updates the repository. Results are reviewed and the process continues until the output is considered ready for load.
5. Post processing and integration – includes the specific requirements for survivorship to represent the required view of party as well as the output formatting and post processing required for the specific target. For load to a CDI or MDM repository this may mean writing the core party data into the appropriate XML notation for a load process.
6. Resources, costs and deliverables on a projected timeline.