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SQL Server Best Practices for Data Quality: Using Melissa’s Data Quality Components for SSIS

SQL Server Best Practices for Data Quality: Using Melissa’s Data Quality Components for SSIS

Accurate data is imperative for an organization to conduct cost effective decision making, marketing promotions, mailings, database bloat impacting performance, storage and more. There is a need to cleanse and validate data on a regular basis to not waste resources. Unfortunately, cleansing and validating data is difficult with the native SQL Server toolset. These technologies will not completely validate, cleanse, match and de-duplicate data.

How do we leverage the SQL Server tool set to achieve these goals?

This whitepaper will guide you through the SQL Server data quality process using five steps to uncover the correct solution.

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