Data quality is an important measure that businesses can use to determine the "fitness" of enterprise information for use in strategic planning, tactical decision-making, and day-to-day operational activities. A lack of data quality continues to pose a major problem for many organizations today as information environments become more and more sophisticated. Disparate applications, databases, systems, messages, and documents make it more difficult than ever to identify and control data quality on an ongoing basis.
Additionally, the massive volume of information generated during the course of a rising number of increasingly complex business transactions, combined with data that flows in from countless third-party sources, can create tremendous challenges for organizations striving to maintain high levels of data quality. As a result, poor or "dirty" data is permeating systems across the enterprise, negatively impacting everything from strategy development and performance management to sales, finance, and customer service.
Solving the problem is not as easy as it sounds. Incomplete or conflicting business rules, different scoring techniques and validation methods, and unclear data requirements that cannot adapt to specific challenges have hindered data quality efforts. In order to enhance key business processes and drive growth with data that is correct, complete, and timely, organizations need a flexible, reliable, and proactive way to preserve the ongoing integrity of their most critical information assets.
The iWay Omni-Gen Data Quality Edition from Information Builders is a comprehensive, unified toolset designed to profile, cleanse, and enrich data. It promotes consistency, accuracy, and completeness across all enterprise information sources, combining a powerful rules engine with a real-time firewall to proactively keep bad data out of any environment.
With iWay, organizations can better control transactional and analytical applications, enhance system migration or software integration projects, improve customer identification processes, validate inputs in self-service and other online applications, and much more by:
- Building a real-time data integrity firewall, complete with real-time reporting and monitoring
- Data profiling and data analysis, to assess its quality and immediately identify and correct any integrity issues
- Dynamically cleansing data via an automated rules engine. Restrictions, constraints, and other data integrity rules can be defined and implemented, then automatically applied to data values across the information landscape, triggering instant changes to existing data to eliminate mistakes
- Enriching information by appending it with relevant content gathered from external sources
- Matching and merging information across multiple data sets to promote consistency, in conjunction with the iWay Omni-Gen Master Data Management and Integration Editions
Find out whether your organization would benefit from real-time data quality solutions in our complimentary white paper: