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SAS® Data Management

Take charge of your data with the industry’s leading integration technology.

Every decision, every business move, every successful customer interaction – they all come down to high-quality, well-integrated data. If you don’t have it, you don’t win. Data management from SAS is an industry-leading solution built on the SAS® Platform that helps you improve, integrate and govern your data.


Boost productivity and work more efficiently.

No matter where your data is stored – from legacy systems to Hadoop – SAS Data Management helps you access the data you need. Create data management rules once and reuse them, giving you a standard, repeatable method for improving and integrating data – without additional cost.

Collaborate easily with other teams.

As an IT expert, it's easy to get entangled in tasks outside your normal duties. SAS Data Management enables your business users to update data, tweak processes and analyze results themselves, freeing you up for other projects. Plus, a built-in business glossary as well as SAS and third-party metadata management and lineage visualization capabilities keep everyone on the same page.

Use one seamless technology, built from the ground up.

SAS Data Management technology is truly integrated, which means you’re not forced to work with a solution that’s been cobbled together. All our components – from data quality to data federation technology – are part of the same architecture.

Feel confident that data is reliable and ready for action.

At SAS, we’re experts at making sure data is prepped for visualization, analytics or operational use. So we promote data quality, transparency and accountability. Our built-in auditing tools monitor processing. Source data lineage helps you know that your data is primed and prepared for analytics.

Integrate, manage and govern big data from Hadoop.

As organizations put more data in Hadoop, you need to get value from that information. We give you fast, easy access to Hadoop via technologies such as Impala or Pivotal HAWQ, allowing you to add big data to existing IT processes. And with transformations for MapReduce, Pig and Hive, you can manage big data where it lives.


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SAS Data Management screenshot on laptop
  • One development environment. Manage processes with an intuitive, role-based GUI that offers drag-and-drop functionality, source system access and a customizable metadata tree.
  • Integrated process designer. Build and edit data management processes with a visual, end-to-end event designer.
  • Superior connectivity and data access. Connect in real time or batch to more data sources on more platforms than most other solutions.
  • Extract, transform and load (ETL) and extract, load and transform (ELT). Gain more flexibility with out-of-the-box SQL-based transforms delivering ELT capabilities.
  • Data governance and metadata management. Enable better collaboration with an integrated business glossary, SAS and third-party metadata management and lineage visualization capabilities.
  • Data federation. Get virtual access to database structures, enterprise applications, mainframe legacy files, text, XML, message queues and other sources.
  • Migration and synchronization. Migrate or synchronize data between database structures, enterprise applications, mainframe legacy files, text, XML, message queues and other sources.
  • Message queuing. Integrate asynchronous business processes via message-based connectivity.
  • Enhanced administration and monitoring. Track metrics with job status and performance reports as well as trending information.
  • SAS Metadata Bridge for Big Data. Import and export metadata from third-party applications for easier access to Hadoop data.
  • Integration of SAS Data Loader for Hadoop. Integrate work with other data flows, and then schedule and monitor it using SAS technologies.

Recommended Resources

Read the SAS Data Management fact sheet.

Read fact sheet

Gartner positions SAS as a Leader in the Gartner Magic Quadrant for Data Integration Tools.

Read analyst report

Learn five data management for analytics best practices.

Read white paper

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