What Is Data Virtualization?
Data virtualization is mostly used as a synonymous with information agility.
It is a simpler, unified view of trusted and verified business data. It is to be provided in real time or near real time as needed by the consuming applications, processes, analytics, or business users.
Data virtualization integrates data from disparate sources, locations and formats, without replicating the data, to create a single "virtual" data layer that delivers unified data services to support multiple applications and users. The result is faster access to all data, less replication and cost, more agility to change.
A visual modeling environment provides flexibility where data scientists developers model data, design services, build transformations, optimize queries, manage resources, and much more....
The query engines securely accesses, queries, federates, abstracts, and delivers data to consuming business solutions. Multiple caching options provide additional speed and flexibility.
A self-service business data directory and data catalog lets users easily search, categorize, and consume IT-curated data. The directory encourages data service sharing and reuse, accelerating business outcomes while reducing IT workloads.
Provides analytics access to corporate assets without the complexity of creating balkanized data warehouses or hard-to-manage extracts.
Examine data, locate important entities, and reveal hidden relationships across distinct data sources. Quickly build and display comprehensive entity relationship diagrams and data models to meet new business requirements.
Adapters connect to databases, files, big data, cloud sources, packaged applications, and more. Beyond schema-to-schema only, adapters integrate with data source optimizers to ensure more accurate queries and higher performance.