DataFlux Data Management Studio: Data Monitoring

Real-time monitoring of data quality – enforcing business rules and building the foundation for data governance

DataFlux provides a single, unified platform to control all aspects of enterprise data management. By creating business rules once and reusing them across applications, you can apply a uniform set of business standards in real time across any system. DataFlux Data Management Studio provides the design, development and monitoring environment for proactive data governance.

Data Management Studio allows you to:

  • Design and enforce rules to determine if data is maintained within proper control limits and meets pre-defined business rules
  • Create data alerts and controls to verify that data remains in compliance with internal and external data policies
  • React to data problems quickly, before the inaccurate or invalid data negatively impacts the business
  • Create customized business rules to validate and audit operational processes
  • Enable enterprise governance, risk and compliance monitoring

DataFlux data monitoring technology uses an advanced service-oriented architecture (SOA) to expose data quality rules as web services to enable ongoing, accurate information. These rules can operate within your existing IT framework, providing regular status checks of data governance procedures.

High-Quality Data for Governance, Risk and Compliance

Data monitoring improves your ability to make sound, informed business decisions by providing an automatic early-warning process for out-of-tolerance data. Data Management Studio allows you to quickly identify and eliminate the costs associated with previously undetected data quality and business rule violations.

With Data Management Studio, business users can easily develop and refine all-encompassing business rules that govern their data, creating the foundation for a complete data governance platform.


White Paper

Observing Data Quality Service Level Agreements

This white paper by David Loshin from Knowledge Integrity examines how to measure data quality and what to do when the data does not meet the level of acceptability.

Webcast

Defining Relevant Metrics for Populating a Data Quality Scorecard

In this webcast, David Loshin from Knowledge Integrity and Dan Soceanu from DataFlux explore ways to qualify data control and measures to support the governance program.