Data Quality

DataFlux data quality solutions allow organizations to cleanse, correct and enhance any type of enterprise data – and create an accurate view of your organization, your customers and your business environment

DataFlux is the recognized industry leader in data quality solutions, offering a single, integrated platform for end-to-end data quality from initial profiling and discovery efforts to ongoing real-time data monitoring. With any corporate business initiative, such as enterprise resource planning (ERP), customer relationship management (CRM) and mergers and acquisitions, problematic data can derail the entire effort. High-quality data is critical for success.

Good data is the basis for solid business decisions. Having an accurate view of your organization, your customers and your business environment allows you to optimize profitability, mitigate risks and reduce costly operational inefficiencies. To create high-quality data that is always available, DataFlux provides industry-leading data quality features and functionality, allowing you to create data services that standardize, correct and integrate data as it arrives in your IT systems.

DataFlux technology enables you to analyze, improve and control enterprise data and successfully address data quality issues, including the ability to:

  • Profile data to discover errors, inconsistencies, redundancies and incomplete information
  • Correct, standardize and verify information across the enterprise from a single platform
  • Match, merge or link data from a variety of disparate sources
  • Enrich data using information from internal and external data sources
  • Check and control data integrity over time with real-time data monitoring, dashboards and scorecards

Data Rationalization, Standardization and Transformation

DataFlux offers an industry-leading platform that allows users to easily rationalize, standardize and transform data across the enterprise. DataFlux technology can help your entire organization understand and improve the quality of your data. The intuitive DataFlux user interface allows business users to control enterprise data management, including the ability to:

  • Automatically validate data and consolidate similar information
  • Create an automatic data rationalization framework
  • Validate and consolidate similar information
  • Consolidate customer records into identifiable customer groups
  • Utilize sophisticated fuzzy matching technology and innovative clustering methodologies

The DataFlux natural language parsing ability and out-of-the box or customized data quality rules allow organizations to rationalize and transform inconsistent data to:

  • Standardize and correct customer, product and other information
  • Automatically identify name, address, phone number, customer ID and any other common customer data element
  • Parse measurements, quantities, packaging information, manufacturer names, product IDs and any other common product data element
 
 

Finding an Upside in the Downturn with Data Quality

In the current macroeconomic malaise, CIOs are left scratching their heads on how to sustain and fund important information management projects such as master data management and data quality. This paper from Ovum, a leading research firm in technology, telecommunications and other business sectors, argues against cutting into these projects too deeply.
 

Real-Time Data Quality

DataFlux data quality capabilities allow your organization to examine and correct data automatically on a transactional basis and enforce business rules in real time throughout the enterprise.

  • Plan and prioritize data correction initiatives
  • Build more consistent, accurate and reliable data across business systems
  • Verify and validate data accuracy to improve the overall accuracy of customer records, product data and other information
  • Apply business rules across the enterprise to ensure all corporate data reflects business needs

Industry Report

Deploying Data Quality Tools Across the Enterprise: No Longer a Luxury

In this report from Gartner Research, DataFlux President and CEO Tony Fisher examines why managing data quality is becoming a business-critical issue for many organizations.

Industry Report

Driving Value from Data: Strategies for Optimizing Information Assets

Recent research by Information Age exposes the wide set of challenges organizations face in their attempts to support critical business issues with effective data governance.

Webcast

Implementing a Data Quality Strategy

In this informative web seminar, DataFlux President and CEO Tony Fisher and analyst Ted Freidman discuss some of the basic issues of data quality, master data management and data governance.

White Paper

Populating a Data Quality Scorecard with Relevant Metrics

This white paper by David Loshin explores ways to qualify data control and measures to support the governance program, and how to determine the measurable business value of fixing data quality issues.