Data Quality procedures are important for data warehousing, ETL, data integration or
business intelligence initiatives. SQL Server and the SSIS environment, available with
SQL Server 2005, are popular choices for such data intensive projects since they handle
millions of records quickly and intuitively.

What is Data Quality?

Data quality usually refers to the completeness and accuracy of data in existing data sets.
Maintaining data quality requires periodical data profiling, data standardization and
deduplication. Data Quality is critical for proper reporting and decision making.
Many companies employ dedicated personnel or data stewards, tasked with assessing and improving the
quality of data.

IST - The Intelligent Choice for SSIS or SQL Server data quality

At IST we utilize our extensive data quality and fuzzy matching expertise to develop
a complete SSIS data quality solution. Our SSIS components include name parsing and
name standardization, address correction and address standardization, merge/purge and
deduplication. These components leverage our industry leading algorithms, combined
with the rich functionality of the Microsoft's SSIS platform to produce a flexible and
robust data quality solution available to anyone who runs SSIS or SQL Server 2005.