“Organizations utilize data in two primary ways:

1. for transactional purposes in running their business
2. for analytic purposes in improving their business.

In either case, clean data is essential for achieving optimal business results. To this end, companies must implement programs to assess, measure, report on, and address data quality risks.

The data quality approach at NSC involves iterative processes including:

• Reviewing the types of risks
• Estimating the opportunity cost of using poor data quality
• Defining data quality expectations
• Developing processes and tools to detect and cleanse data
• Assessing data quality
• Producing reporting, tracking, and root cause analysis

To carry out these operations, NSC employs specialized tools and a team of IT experts.