Data Virtualization integrates data sources across multiple types and locations and turns all this data into one logical data view. This virtual data lake makes the job of getting value out of your data easy.
After creating connections to your data sources, you can quickly view across your organization’s data. This virtual data platform enables real-time analytics without moving data, duplication, ETLs, or additional storage requirements, so processing times are greatly accelerated. You can bring real-time insightful results to decision-making applications or analysts more quickly and dependably than methods that don’t use virtualization.
Centralized authentication and authorization are enforced for platform users to access data sources in a trusted environment. The Data Virtualization Admin, Data Virtualization Engineer, Data Virtualization Steward, and Data Virtualization User roles provide granular access management to the virtualized assets. Cloud Pak for Data users that need to use Data Virtualization functions must be assigned specific Data Virtualization roles based on their job description.
All communication between the environment and the application is securely encrypted with robust IBM technology, and SSL/TLS encryption by using standard protocols.
Data Virtualization supports queries by using standard SQL through common interfaces including R, Spark, Python, and Jupyter Notebooks. In addition, queries are also supported by the most common analytics application tools, including IBM Watson Studio and Cognos Analytics.
|Db2 Data Management Console||Administer, monitor, manage, and optimize the performance of your IBM Db2 databases.|
|Watson Knowledge Catalog||Create catalogs of curated assets with this secure enterprise catalog management platform that is supported by a data governance framework.|
See Supported data sources for a list of data source services that are compatible.