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Company Information |
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DataFlux
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Overview |
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DataFlux enables organizations to analyze, improve and control their data through an integrated technology platform. With DataFlux enterprise data quality and data integration products, organizations can more effectively and efficiently build a unified view of customers, products, suppliers or any other corporate data asset. A wholly owned subsidiary of SAS (www.sas.com), DataFlux helps customers rapidly assess and improve problematic data, and build the foundation for enterprise data governance. Effective data governance delivers high-quality information that can fuel successful enterprise efforts such as risk management, operational efficiency and master data management (MDM). |
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Services Offered |
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- Data Quality
- Data Governance
- Master Data Management
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Request More Information from This Company |
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Featured Content from DataFlux
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- MDM Components & The Maturity Model
This white paper by David Loshin provides a conceptual outline of technical MDM components and examines how those components relate to the levels of organizational maturity determined by the ability to provide MDM services. This model offers ways in which enterprise architects can target a desired level of MDM maturity to develop and design an implementation roadmap that shows the way towards successfully integrating the necessary MDM components at the correct stages.
- The Data Governance Maturity Model
This DataFlux white paper introduces the Data Governance Maturity Model and explains how your organization can use this model to understand the major issues of building better data across the enterprise, to learn to utilize existing resources to achieve more effective data quality policies, and how to find a data governance strategy that fits your organization.
- Five Steps to More Valuable Enterprise Data
Companies worldwide struggle with inconsistent, inaccurate or unreliable data - and often don't know how to build more useful corporate information. This white paper examines a five-step method for improving your data, using data profiling, data quality, data integration and other methods to find and fix bad data.
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