North Shore Credit Union (NSCU) has chosen AMB as its data quality provider to cleanse old system data as part of the organization’s data governance program.

 

NSCU officials said that they embarked on a banking software conversion and in its preparation the data migration team searched for a data quality and data profiling tool that would help cleanse data from the old system and complement the ETL process for business intelligence (BI).

 

The mid-sized Canadian credit union with 44,000 members and 12 branches searched for a tool that would provide a cost-effective solution and integration with Microsoft (News - Alert) technology. NSCU picked AMB’s Predictive Data Management SOA solution, which is armed with Microsoft SSIS integration and InfoExpose providing insights into the data and real-time analysis for duplicates and sigma deviations. NSCU officials said that AMB’s solution helps with the data migration and fraud detection, which is a critical task for any financial institution.

 

AMB said that the tight integration with ETL tools and the availability of integrated SOA components and tools usable by their stakeholders was a key differentiator for choosing the solution.

 

Steve Meister, president of AMB welcomed NCSU as a valued customer, as AMB continue expanding their goal to provide unparalleled data profiling and governance solutions to the marketplace that significantly improve the state of data quality present in many organizations. Meister said that AMB will continue to be the leader in technology and customer satisfaction while delivering enormously beneficial and affordable solutions that allow their customers to obtain viral participation in their data governance programs that deliver on the promise of trustworthy data.

 

According to Mark Albala, a data governance practitioner, author and AMB Advisory Board Member, the tight integration of tools and process delivered by AMB’s Predictive Data Management suite and remarkable ease of use, make PDM a knockout solution for data governance.

 

“Being able to integrate data profiling and cleansing tools as an in-stream component of an overall governance program to administer a repeatable process, is what this industry has promised all along. I am pleased to serve on the board of AMB because Predictive Data Management delivers on this promise,” he said.

 

Earlier this year, AMB introduced two new features unique to the industry that enhances its suite of data discovery and cleansing capabilities. By applying profiling techniques to numeric data, AMB-PDM’s new Outlier Discovery feature helps identify data anomalies that skew the results of corporate data and compromises data quality. The company announced that along with AMB-PDM’s new Match Merge feature, their product suite will also provide corporations the ability to discover data issues related to reference, descriptive and numeric data.