Data quality

SAS Data Quality

Build a data-driven business and make decisions you can trust.

SAS is a Leader: 2022 Gartner^® Magic Quadrant^™ for Data Quality Solutions

Become data-driven, and make better decisions using data you can trust.

Improve your data where it exists.

SAS Data Quality meets you where you are, addressing your data quality issues without requiring you to move your data. You’ll work faster and more efficiently – and, with role-based security, you won’t put sensitive data at risk.

Manage the entire data quality life cycle.

Data quality isn’t something you do just once; it’s a process. We help you at every stage, making it easy to profile and identify problems, preview data, and set up repeatable processes to maintain a high level of data quality.

Build on decades of data quality experience.

Only SAS delivers this much breadth and depth of data quality knowledge. We’ve experienced it all – and integrated that experience into our products. We know that data quality can mean taking things that look wrong and seeing if they’re actually right. How? With matching logic. Profiling. Deduplicating. And – above all else – innovating.

Promote collaboration.

SAS Data Quality gives business users the power to update and tweak data themselves, so IT is no longer spread too thin. Out-of-the-box capabilities don’t require extra coding. Enhanced SAS and third-party metadata management, visualization and reporting keep everyone on the same page.

Key Features

Data quality is a key component of our analytics platform, and we can help you put it at the core of everything you do. We support traditional relational databases, data lakes, cloud offerings, on-site and hybrid data architecture deployments.

View detailed features list

Data cleansing

Correct nonstandard or duplicate records as well as unknown data types.

Entity resolution

Identify individuals across multiple data sources from incomplete relationships.

Unified web-based console

Monitor data quality jobs, and view data issues and governance activities.

Foundational master data management

Achieve a single view across multiple sources for one domain.

Business glossary & lineage

Align business and IT, relate business and technical metadata, and visualize how changes affect other data assets.

Visualization & reporting

Create reports and share information about data management initiatives as well as monitor data health and status of remediation issues.

Data integration

Embed data quality into extract, transform and load (ETL) and extract, load and transform (ELT) activities from multiple sources.

Data remediation

Route decisions about data issues to the right data steward or DBA for resolution.

In-database technologies

Shorten the time needed for key data quality and analytical processes by carrying out data quality and scoring functions in the database.

View fact sheet

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