SAS Data Quality Features List

Data cleansing

  • 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.

      Data monitoring

      • 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.

      Data profiling

      • 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.

          Entity resolution

          • 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.

          Data integration

          • 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.

          Data remediation

          • 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.