Without data that is reliable, accurate, and updated, organizations can’t confidently distribute that data across the enterprise, leading to bad business decisions. Faulty data also hinders the successful integration of data from a variety of data sources. But with a sound data quality methodology in place, you can integrate data while improving its quality and facilitate a master data management application—at low cost.
Model , Data Quality Objectives , Data Quality Plan , Data Quality Problems , Data Quality Process , Data Quality Products , Data Quality Program , Data Quality Project , Data Quality Report , Data Quality Reporting . Six Steps to Managing Data Quality with SQL Server Integration Services (SSIS) Introduction A company's database is its most important asset. It is a collection of information on customers, suppliers, partners, employees, products, inventory, locations, and more. This data is the foundation