SAS Data Management Features
Data Source Access (3)
Breadth of Data Sources
Provides a wide range of possible data connections, including cloud applications, on-premise databases, and big data distributions, among others
Ease of Data Connectivity
Allows businesses to easily connect to any data source
API Connectivity
Offers API connections for cloud-based applications and data sources
Data Interaction (8)
Profiling and Classification
Permits profiling of data sets for increased organization, both by users and machine learning
Metadata Management
Indexes metadata descriptions for easier searching and enhanced insights
Data Modeling
Tools to (re)structure data in a manner that enables quick and accurate insight extraction
Data Joining
Allows self-service joining of tables
Data Blending
Provides the ability to combine data sources into one data set
Data Quality and Cleansing
Allows users and administrators to easily clean data to maintain quality and integrity
Data Sharing
Offers collaborative functionality for sharing queries and data sets
Data Governance
Ensures user access management, data lineage, and data encryption
Data Exporting (3)
Breadth of Integrations
Provides a wide range of possible integrations, including analytics, data integration, master data management, and data science tools
Ease of Integrations
Allows businesses to easily integrate with analytics, data integration, master data management, and data science tools
Data Workflows
Operationalizes data workflows to easily scale repeatable preparation needs
Administration (4)
Data Modelling
Tools to (re)structure data in a manner that allows extracting insights quickly and accurately
Recommendations
Analyzes data to find and recommend the highest value customer segmentations.
Workflow Management
Tools to create and adjust workflows to ensure consistency.
Dashboards and Visualizations
Presents information and analytics in a digestible, intuitive, and visually appealing way.
Compliance (4)
Sensitive Data Compliance
Supports compliance with PII, GDPR, HIPPA, PCI, and other regulatory standards.
Training and Guidelines
Provides guidelines or training related to sensitive data compliance requirements,
Policy Enforcement
Allows administrators to set policies for security and data governance
Compliance Monitoring
Monitors data quality and send alerts based on violations or misuse
Data Quality (3)
Data Preparation
Curates collected data for big data analytics solutions to analyze, manipulate, and model
Data Distribution
Facilitates the disseminating of collected big data throughout parallel computing clusters
Data Unification
Compile data from across all systems so that users can view relevant information easily.
Functionality (5)
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Identification
Correctly identify inaccurate, incomplete, or duplicated data from a data source.
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Correction
Utilize deletion, modification, appending, merging, or other methods to correct bad data.
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Normalization
Standardize data formatting for uniformity and easier data usage.
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Preventative Cleaning
Clean data as it enters the data source to prevent mixing bad data with cleaned data.
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Data Matching
Finds duplicates using the fuzzy logic technology or an advance search feature.
Management (10)
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Reporting
Provide follow-up information after data cleanings through a visual dashboard or reports.
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Automation
Automatically run data identification, correction, and normalization on data sources.
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Quality Audits
Schedule automated audits to identify data anomalies over time based on set business rules.
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Dashboard
Gives a view of the entire data quality management ecosystem.
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Governance
Allows user role-based access and actions to authorization for specific tasks.
Business Glossary
Lets users build a glossary of business terms, vocabulary and definitions across multiple tools.
Data Discovery
Provides a built-in integrated data catalog that allows users to easily locate data across multiple sources.
Data Profililng
Monitors and cleanses data with the help of business rules and analytical algorithms.
Reporting and Visualization
Visualize data flows and lineage that demonstrates compliance with reports and dashboards through a single console.
Data Lineage
Provides an automated data lineage functionality which provides visibility over the entire data movement journey from data origination to destination.
Security (3)
Access Control
Authenticates and authorizes individuals to access the data they are allowed to see and use.
Roles Management
Helps identify and manage the roles of owners and stewards of data.
Compliance Management
Helps adhere to data privacy regulations and norms.
Maintainence (2)
Data Quality Management
Defines, validates, and monitors business rules to safeguard master data readiness.
Policy Management
Allows users to create and review data policies to make them consistent across the organization.
Generative AI (5)
AI Text Generation
Allows users to generate text based on a text prompt.
AI Text Summarization
Condenses long documents or text into a brief summary.
AI Text Generation
Allows users to generate text based on a text prompt.
AI Text Generation
Allows users to generate text based on a text prompt.
AI Text Summarization
Condenses long documents or text into a brief summary.
Agentic AI - Data Governance (6)
Autonomous Task Execution
Capability to perform complex tasks without constant human input
Multi-step Planning
Ability to break down and plan multi-step processes
Cross-system Integration
Works across multiple software systems or databases
Adaptive Learning
Improves performance based on feedback and experience
Natural Language Interaction
Engages in human-like conversation for task delegation
Decision Making
Makes informed choices based on available data and objectives




