SAS Data Quality Features List
- Correct nonstandard or duplicate records as well as unknown data types.
- Establish data hierarchies and reference data definitions.
- Gain more value from data by separating values as required through natural language parsing.
- Customize data quality rules to suit your needs with both customer and product data.
- Design and enforce rules to determine if data is maintained within proper control limits and meets predefined business rules.
- Create data alerts and controls to verify that data remains in compliance with internal and external policies.
- Validate data against standard measures and customized business rules.
- Uncover relationships across tables, databases and source applications.
- Verify that the data in your tables matches the appropriate description.
- Establish trends and commonalities in business information and examine numerical trends via mean, median, mode and standard deviation.
SAS Viya Address, Email & Phone Verification
- Verify, standardize and enrich data from any country or territory in the world.
- Resolve address, geocode, email and phone data quality issues.
- For additional details on licensing address/email/phone enrichment & verification solutions, please refer to our partner page.
- Identify individuals across multiple data sources from incomplete relationships.
- Manage entity resolution routines through advanced fuzzy-matching technology.
- Create multirecord clusters, confidence scores and scatter plots to determine potential clusters.
- Recognize when slight variations suggest a connection between records.
Data management console
- Monitor data quality jobs and view data issues and governance activities.
- Access all data management activity from a single, common control point.
- Secure role-based access and actions to authorization for specific data quality tasks.
- Avoid logging in to a different web page or panel when moving from one function of the data management platform to another.
- Embed data quality into extract, transform and load (ETL) and extract, load and transform (ELT) activities from multiple sources using both traditional batch processing and in-database methods.
- Transfer data to new or different locations while improving the accuracy and consistency of data through data migration.
- Match information within or across data sources, standardizing formatting differences.
SAS Business Data Network & SAS Lineage
- Collaborate on the creation and management of business terms and relationships with technical metadata.
- Manage who has access to different types of business terms and metadata.
- Visualize and trace data from source to consumer.
- Document data changes and transformations.
- View point-in-time snapshots of past terms and relationships to meet auditing requirements.
- Streamline integration with other applications via the public REST API.
- Route or correct data issues identified during data management operations.
- Engage data stewards and IT through a workflow-driven process.
Visual process orchestration & job monitoring
- Manage SAS and third-party technologies in a single process.
- Minimize or eliminate dependence on third-party scheduling systems and shell scripting for job control.
- Control the execution of multistep and multijob processes.
- Coordinate SAS and third-party jobs to work in a cohesive managed bundle.
- Log in and monitor the status of data management jobs without having to go to various dedicated servers to pull information.