Dynamic data virtualization tools.

Go beyond traditional data virtualization by selecting what, where, when, and how  to virtualize.

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Agile data integration

icons_Data Virtualization-Perform Live

Perform live

Connect to data, and deliver it 
in milliseconds 

icons_Data Virtualization-Have it your way

Have it your way

Choose which data to virtualize, 
and which to store

Data Virtualization Enrichment

Inject insights

Enrich data in real-time, 
for operational intelligence

A unique virtual view

Dynamic Data  Virtualization
Dynamic Data  Virtualization

Dynamic data virtualization tools ingest data from any source, unify it according to a semantic layer, optionally store it (physically or in memory), transform and enrich it, employ data masking –via data masking tools – when required, and ultimately make it available to consuming applications and data analysts.

Get more out of
data virtualization tools

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Data abstraction turns data into business


Dynamic data virtualization tools take the complexity out of accessing data from a wide range of underlying data sources, formats and structures.

They provide access to live data through a logical abstraction layer whose schema is the collection of all tables and fields for a particular business entity. This abstraction layer is called a data product schema, and a Data Product Platform can manage multiple schemas (for multiple business entities), including the relationships between them.

In the case of a customer business entity, for example, the customer data product includes a schema that unifies all the information about a customer from all underlying systems. This is especially useful in Customer 360 initiatives.

Virtualize or store –
it’s your call

data-virtualization Virtualize-or-store
data-virtualization Virtualize-or-store

Dynamic data virtualization tools give you the flexibility to decide which of the data product’s data will be virtualized – unified, transformed, orchestrated, and delivered from source to target – and which data will be stored physically in a Micro-Database™.

Storing some of the data, rather than completely virtualizing it, is an advantage when you’d like to:

  • Minimize the burden on your source systems, by storing data that doesn’t change on an ongoing basis, instead of accessing it from the source every time.
  • Enrich the data with new fields that do not exist in your underlying source applications.
  • Implement Reverse ETL.
  • Maintain a log for the changes made to the data product instance, to compare its content over time (e.g., in tracking configuration changes made to a specific device at a customer's site).

Top-Rated on Gartner

See how Vodafone implemented Data Product Platform for multiple use cases, including Customer Data Platform / Hub and Test Data Management, to deliver strategic business
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Access the data in any method


Data Product Platform enables authorized data consumers with seamless access to the data they need via SQL, or web service APIs. Alternatively, the data can be delivered ("pushed") to the data consumers via data streaming or messaging methods.

Dynamic data virtualization tools assure unmatched high-speed, high-scale data delivery, from source systems to data consumers.

Dynamize your data virtualization tools

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