Augmented data quality – driven by AI/ML, metadata, convergence and integrations across data management offerings for useful automation – continues to be the key driver in this market. This research allows data and analytics leaders to understand the vendor landscape and make the best choice.
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- Analyst Report Gartner positions SAS as a Leader in the Magic Quadrant for Data Quality SolutionsGartner positions SAS as a Leader in the Magic Quadrant for Data Quality Solutions.
- Customer Story A data-driven approach to whole person careRiverside County relies on data integration and analytics from SAS to improve the health and well-being of vulnerable Californians.
- White Paper The SAS Data Governance Framework: A Blueprint for SuccessThis white paper explains how to build a comprehensive data governance framework that encompasses all parts of the data management infrastructure.
- Article Data management backgrounderFrom data integration to data quality and data preparation, find out what these terms mean and why they’re so important for your analytics projects.
- White Paper I Spy PII: How to Use SAS® Data Management for Personal Data ProtectionGet a step-by-step look at how to use SAS Data Management software to access, identify, govern, protect and audit personal data across your organization.
- White Paper The General Data Protection Regulation: What It Means and How SAS® Data Management Can HelpFind out how the GDPR could affect your business and how SAS Data Management solutions can help you prepare.
- White Paper Improving Data Preparation for Business AnalyticsThis TDWI Best Practices Report discusses the latest data preparation processes, self-service options and how to effectively integrate data prep with analytics and BI solutions.
- Article Data governance: The case for self-validationLearn why you should redefine data governance policies to empower customers to be accountable for keeping their personal data accurate, consistent and up-to-date.
- White Paper Data Quality Challenges and PrioritiesFind out how organizations are addressing their most pressing data quality issues, discover the top 10 priorities for data quality solutions, and learn the best ways to engage and empower business users to improve data quality.
- Article Components of an information management strategyBefore starting a data management strategy for your business, you need to understand each component. Data expert David Loshin breaks them down.
- White Paper Populating a Data Quality Scorecard with Relevant MetricsExplore ways to qualify data control and measures to support a data governance program, and learn how data management practitioners can define metrics that are relevant to how specific data-quality issues affect their business.
- White Paper Building a Data Quality Scorecard for Operational Data GovernanceLearn how to take the concepts of data governance into general practice as a byproduct of the processes of inspecting and managing data quality control.
- White Paper Building an Analytical Culture for SuccessAn ambitious, culture-centric project reshaped people’s attitudes about data and quickly returned more than a $1 million in cost savings. See the six guiding principles that led to success where three earlier attempts had failed.
Gartner, 2022 Magic Quadrant for Data Quality Solutions by Ankush Jain, Melody Chien. 1 November 2022. SAS was recognized as DataFlux from 2006-2012. Gartner and Magic Quadrant are registered trademarks and service marks of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved. This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.