SAS Data Management Product Overview
SAS Data Management is a comprehensive and integrated platform designed to address the complex data management needs of modern IT organizations. This solution is tailored to improve performance, functionality, and governance of data management infrastructure, enabling organizations to treat their data as a valuable business asset.
Key Objectives
- Centralized Data Management: SAS Data Management provides a unified platform to manage, govern, and secure data, eliminating the need for multiple, disparate tools and technologies.
- Data Quality and Integrity: The platform embeds data quality into every process, ensuring that data is accurate, consistent, and reliable.
- Enhanced Collaboration: It facilitates collaboration between business users and IT teams through a user-friendly interface and robust metadata management.
Key Features and Functionality
Data Integration and Processing
- Extraction, Transformation, and Load (ETL) and Extraction, Load, and Transformation (ELT): Simplify data integration with over 300 out-of-the-box SQL-based transforms for creating, joining, inserting, deleting, updating, and merging data. The platform supports both batch and real-time processing through message queues and web services.
Data Governance and Metadata Management
- Data Discovery and Classification: Identify and classify data and metadata through data discovery processes. Track data lineage and history, and monitor these processes in real-time using dashboards.
- Access Control and Permissions: Establish and manage user permissions, ensuring that data access is secure and compliant with organizational policies.
Data Federation
- Unified Access: Provide consistent business views across multiple data sources without physically moving the data. Users can access data through a single query or dashboard, regardless of where the data is stored.
Data Quality and Enrichment
- Automated Validation and Standardization: Embed data quality into every process, including profiling, standardizing, matching, and monitoring. Customizable rules and automated processes ensure data conforms to corporate standards.
- Fuzzy Matching and Clustering: Use sophisticated fuzzy-matching technology to validate and consolidate master records into identifiable data groups.
Master Data Management
- Semantic Data Descriptions: Use semantic data descriptions to uniquely identify business elements such as customers, products, and accounts. This feature helps in maintaining data integrity and consistency across the organization.
- Real-Time Data Monitoring: Monitor data integrity in real-time using dashboards and scorecards, ensuring continuous validation and correction of master data.
Migration and Synchronization
- Data Migration and Sync: Manage data migration and synchronization issues arising from mergers, acquisitions, or business growth. The platform ensures consistent data across disparate systems through embedded, reusable data quality rules and real-time data services.
Advanced Analytics and AI
- Event Stream Processing: Analyze streaming data in real-time, determining which data requires immediate attention. This is achieved using prebuilt operators, functions, and advanced analytics.
- Artificial Intelligence and Machine Learning: Incorporate AI capabilities such as natural language processing to manage data accurately. Self-tuning systems and fuzzy matching enhance data quality and integrity.
Administration and Monitoring
- Enhanced Administration: Provide administrators with greater visibility into system usage, configuration settings, and resource utilization. This helps in managing capacity effectively and preventing performance issues.
- Reporting and Analytics: Offer reporting capabilities that provide business intelligence functionalities, enabling decision-makers to understand the status of their IT environment in real-time.
Benefits
- Improved Efficiency: Reduce time spent on data preparation and increase productivity through automated and streamlined processes.
- Enhanced Collaboration: Facilitate collaboration between IT and business users through a common platform and intuitive interface.
- Better Decision Making: Ensure access to clean, well-governed data at the right time and in the right format, enabling better decision-making.
- Compliance and Security: Implement robust data governance and security measures to ensure compliance with organizational policies and reduce risk exposure.
In summary, SAS Data Management is a powerful tool that integrates various aspects of data management, from data integration and quality to governance and analytics, providing a unified solution for organizations to manage their data effectively and drive business success.