iWay DQC is the hub for data quality management in your organization. It delivers centralized management for business rules, data quality, and data flows. iWay DQC also enables the integration and management of data from external master data systems and other data sources, with a single data quality platform.

iWay DQC provides the following capabilities.

• Profiling. Profiling is the analysis of data to provide insight into the data quality. Frequently performed during the initial stage of a project, profiling produces statistics (metadata) about the data that you will be working with. It reveals the general level of data quality, enabling you to identify quality issues at the outset of a project. Profiling is especially useful when you are working with a large amount of data.

  For fast data analysis, iWay DQC uses advanced semantic profiling.

• Parsing and standardization. Parsing is the decomposition of a field into its component parts. Standardization applies consistent formats to field values, based on industry standards, local standards (for example, postal authority standards for address data), user-defined business rules, and knowledge bases that consist of values and patterns.
• Cleansing. Cleansing is the modification of data values to satisfy domain restrictions, integrity constraints, or other business rules that define data quality for your organization. With cleansing, inaccurate data from a data source is detected and corrected or removed. Cleansing ensures that a given set of data is complete, accurate, and valid, making the data meaningful and useful. Cleansing minimizes data errors and improves business performance.
• Matching. Matching is identifying, then linking or merging, related entries within or across sets of data.
• Enrichment. Enrichment is the enhancement of internally stored data by appending related attributes from external sources (for example, consumer demographic attributes or geographic descriptors).
• Monitoring. Monitoring is the deployment of controls to ensure ongoing conformity of data to the business rules that define data quality for your organization.