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Global Intelligence Blog

Insights and Analysis for the Data-Driven Enterprise

Webinar Overview of Data Quality Tools/Components for SSIS

Blog Administrator | Uncategorized | cleanse contact data, data governance, data quality, data quality components, data quality tools, demographic data, enrich data, match data, Metadata, profile data, standardize, unacceptable data

 

For those of you who didn’t make it to Melissa Data’s first webinar this morning, here’s what you missed:

Ira Whiteside, a BI architect, and Bud Walker, a product manager for Melissa Data, showed listeners how to reduce the overall total cost of ownership (TCO) of MDM, data quality, metadata, and data governance efforts through the use of Melissa Data’s Data Quality Components for Microsoft’s SQL Server Integration Services (SSIS).

Attendees learned how to:

    • Profile data to avoid unnecessary processing of unacceptable data


    • Standardize and cleanse contact data

    • Match data for a single, unified view

• Enrich data with latitude and longitude information, demographic data, and more.

October 13, 2010April 5, 2021

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All data goes bad (up to 25% per year), whether due to data entry errors or the simple fact that consumers change jobs, move, update email addresses, marry, etc. At Melissa, we help companies harness the value of their Big Data, legacy data, and people data (names, addresses, phone numbers, and emails) to drive insight, maintain data quality, and support global intelligence.

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