About SAS Data Integration

Data integration is the process of consolidating data from a variety of sources in order to produce a unified view of the data. SAS supports data integration in the following ways:
  • Connectivity and metadata. A shared metadata environment provides consistent data definition across all data sources. SAS software enables you to connect to, acquire, store, and write data back to a variety of data stores, streams, applications, and systems on a variety of platforms and in many different environments. For example, you can manage information in Enterprise Resource Planning (ERP) system, relational database management systems (RDBMS), flat files, legacy systems, message queues, and XML.
  • Data cleansing and enrichment. Integrated SAS Data Quality software enables you to profile, cleanse, augment, and monitor data to create consistent, reliable information. SAS Data Integration Studio provides a number of transformations and functions that can improve the quality of your data.
  • Extraction, transformation, and loading. SAS Data Integration Studio enables you to extract, transform, and load data from across the enterprise to create consistent, accurate information. It provides a point-and-click interface that enables designers to build process flows, quickly identify inputs and outputs, and create business rules in metadata, all of which enable the rapid generation of data warehouses, data marts, and data streams.
  • Migration and synchronization. SAS Data Integration Studio enables you to migrate, synchronize, and replicate data among different operational systems and data sources. Data transformations are available for altering, reformatting, and consolidating information. Real-time data quality integration allows data to be cleansed as it is being moved, replicated, or synchronized, and you can easily build a library of reusable business rules.
  • Data federation. SAS Data Integration Studio enables you to query and use data across multiple systems without the physical movement of source data. It provides virtual access to database structures, ERP applications, legacy files, text, XML, message queues, and a host of other sources. It enables you to join data across these virtual data sources for real-time access and analysis. The semantic business metadata layer shields business staff from underlying data complexity.
  • Master data management. SAS Data Integration Studio enables you to create a unified view of enterprise data from multiple sources. Semantic data descriptions of input and output data sources uniquely identify each instance of a business element (such as customer, product, and account) and standardize the master data model to provide a single source of truth. Transformations and embedded data quality processes ensure that master data is correct.