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DataFlux Adds Data Governance, Workflow Enhancements to Master Data Management Solution

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DataFlux , a leading provider of data management solutions, today announced the release of the DataFlux qMDM Solution v3.0, the latest release of its enterprise MDM technology designed from a single data management framework. This version of DataFlux qMDM includes an enhanced user interface to provide more comprehensive data governance and workflow controls for data stewards and data analysts, giving business users more control over the MDM continuum.

DataFlux qMDM reflects the company’s approach to deliver MDM technologies that provide rapid benefits to the business. In the past few years, organisations have struggled with complex, IT-centric MDM programmes that required high levels of support from consultants and systems integrators – resulting in budget overruns and delayed results. DataFlux qMDM provides technologies designed for both business and IT teams, allowing organisations to closely align the MDM programme to existing data management initiatives – and quickly realise the value of their MDM deployments.

“We’ve seen impressive adoption of DataFlux qMDM in recent months, and a large part of that success is that organisations can no longer afford the ‘blank cheque’ mentality of previous large-scale MDM deployments,” said Tony Fisher, president and CEO of DataFlux. “With this release of DataFlux qMDM – and our acquisition of Baseline Consulting from earlier in the year – DataFlux can provide an end-to-end, enterprise-level MDM solution, from management consulting to full-lifecycle data management solutions.”

DataFlux qMDM fully leverages the DataFlux Data Management Platform, which provides a single platform for data quality and data integration technologies.  DataFlux qMDM v3.0 provides more features to push data governance tasks to the business user throughout the MDM programme, including:

  • Role-based interfaces – Meet both internal and external data policy compliance by providing access to protected information (such as National Insurance numbers or other personal information) to only a certain group or user type
  • Enhanced collaboration on workflows – Implement “collaborative MDM” using DataFlux qMDM to enable the creation, modification and process management of the best surviving record across internal applications
  • Improved visualisations – A revised master data dashboard provides at-a-glance data quality and data governance metrics across entity types and contributing source systems

The key to DataFlux qMDM is the ability to deploy the right technology for the right situation. DataFlux qMDM includes a configurable data hub and multi-domain data model that allows users to create a master view of customers, products, inventory, materials, assets and virtually any other data type. Users will also enjoy additional features, such as:

  • Metadata discovery and data profiling – Begin the MDM deployment with a solid understanding of the data landscape – and jump-start the MDM project
  • Entity resolution and matching – Engage a patented data matching engine to create and maintain a master record
  • Data stewardship – Control the master data hub, as well as the processes and workflows that govern the creation of master data, through an intuitive, business-focused interface
  • Data quality improvement – Utilise DataFlux best-of-breed data quality technology to standardise and rationalise data during the MDM lifecycle
  • Hierarchy management – Manage inter-related data elements, including tiered and networked hierarchical structures
  • Survivorship – Validate master data representations through entity definition, resolution, best record selection/editing and the creation of a universal identifier
  • Data integration – Engage both batch and real-time data integration processes to manage the master hub repository
  • Reporting – Monitor the master repository and the MDM process through interactive dashboards and scorecards
  • Data lifecycle management – Manage the entire data management process, including data loading, data updating and data management
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