ETL and ELT
SAS Enterprise Data Integration Server enables organizations to extract, transform and load (ETL) data from across many different sources to create consistent, accurate information. A point-and-click process design desktop makes it easy to build logical workflows, quickly identify input and output data flows, and create business rules in metadata, all of which enable the rapid generation of data warehouses, data marts and data streams.
SAS also supports the ELT approach of extracting data, loading it into a target database and using database capabilities to transform the data directly within the database (ELT). You simply define whether a process runs in-database or within SAS.
In addition, SAS provides organizations with the flexibility to go beyond the prepackaged transformations to build unique routines without fear of losing vendor support for custom work.
- Enables rapid generation of data warehouses, data marts and data streams.
- Lets you create ETL processes that are reusable, easily modified and have embedded data quality processing.
- Increases returns on existing IT investments by providing multiple-platform scalability and interoperability.
- Provides a choice of executing data integration processes within SAS or within a database.
- A powerful, yet easy-to-use transformation user interface that supports collaboration, reuse of processes and common metadata.
- Single or multiple-source data acquisition, transformation, cleansing and loading to create data warehouses, data marts, or BI and analytic data stores.
- Metadata is captured and documented throughout the data integration and transformation processes and is available for immediate reuse.
- Transformations can run on any platform with any data source.
- More than 300 predefined table and column-level transformations.
- Ready-to-use analytical transformations, including correlations and frequencies, distribution analysis and summary statistics.
- Transformation Generator wizard or Java plug-in design templates for creating reusable and repeatable transformations that are tracked and registered in metadata.
- Transformation processes are callable through custom exits, message queues and Web services, so they are reusable in many different projects and different technology environments.
- Transformations can be executed interactively and scheduled to run in batch at set times or based on events that trigger execution.
- Framework for publishing information to archives, a publishing channel, e-mail or various message-queuing middleware.
- Easily refresh, append and update during loading.
- Optimize loading techniques with user-selectable options.
- Database-aware loading techniques, including bulk load facilities, index and key creation, and dropping and truncating of tables.
- Ability to easily design, create and load OLAP cubes.
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