Melissa Data Completes the Data Quality Circle with Addition of Profiler Tool for SQL Server Integration Services
Flagship SSIS Developer Suite Now Enables Data Assessment and Continuous Monitoring Over Time; Webinar Adds Detail for SSIS Experts
Rancho Santa Margarita, CALIF – March 17, 2015 – Melissa Data, a leading provider of contact data quality and address management solutions, today announced its new Profiler tool added to the company’s flagship developer suite, Data Quality Components for SQL Server Integration Services (SSIS). Profiler completes the data quality circle by enabling users to analyze data records before they enter the data warehouse and continuously monitor level of data quality over time. Developers and database administrators (DBAs) benefit by identifying data quality issues for immediate attention, and by monitoring ongoing conformance to established data governance and business rules.
Register here to attend a Live Product Demo on Wednesday, March 18 from 11:00 am to 11:30 am PDT. This session will explore the ways you can use Profiler to identify problems in your data.
“Profiler is a smart, sharp tool that readily integrates into established business processes to improve overall and ongoing data quality. Users can discover database weaknesses such as duplicates or badly fielded data – and manage these issues before records enter the master data system,” said Bud Walker, director of data quality solutions, Melissa Data. “Profiler also enforces established data governance and business rules on incoming records at point-of-entry, essential for systems that support multiple methods of access. Continuous data monitoring means the process comes full circle, and data standardization is maintained even after records are merged into the data warehouse.”
Profiler leverages sophisticated parsing technology to identify, extract, and understand data, and offers users three levels of data analysis. General formatting determines if data such as names, emails and postal codes are input as expected; content analysis applies reference data to determine consistency of expected content and field analysis determines the presence of duplicates.
Profiler brings data quality analysis to data contained in individual columns and incorporates every available general profiling count on the market today; sophisticated matching capabilities output both fuzzy and exact match counts. Regular expressions (regexes) and error thresholds can be customized for full-fledged monitoring. In addition to being available as a tool within Melissa Data’s Data Quality Components for SSIS, Profiler is also available as an API that can be integrated into custom applications or OEM solutions.