Data Liberation

Integrated data without integration

The 3 Steps of Data Collaboration

Data Liberation
Data Productization
Data Collaboration

Your applications control your data. 

This is a REAL problem for your organization.

It limits the ability to get data to the people and systems that need it, to create new solutions, and to drive better business outcomes.

Why the state of your data is so important?

Most enterprise data realizes less than half of its potential. It's fragmented, buried deep in applications, stuck in legacy systems, or hidden behind vendor paywalls.

Without proper accessibility and availability, the true value of data cannot be realized.

Poor Availability

With architectures such as data warehouses, data lakes and data visualization, the data is only made available to “serve” specific applications. Data cannot be extended to create new solutions.

Poor Accessibility

Data not being readily accessible leads to ongoing data duplication. Copies being made as each new application is built and deployed, creating perpetual fragmentation and data silos.

The majority of today's enterprise data is difficult to connect, collaborate on, and control at scale. Data sets are tied to specific applications and bound to third-party vendors.

Data is confined to limited use, dictated by each separate application.

It's time for a different kind of data

Data being tied to specific applications is an artifact of the way data technology developed from the early mainframe computers: first came the app, then came its data. As database technology advanced, this relationship remained the same, the app-data relationship worked well enough.

In today's advanced architectures continuing to use data models that require endless, ongoing integrations ultimately lead to their collapse,  from inherent and overwhelming levels of complexity. 

The era of application-independent data has arrived!

A model of simplicity now exists where data is freed from being controlled.. to being in control.

A data network where bi-directional connectivity freely places data in and out of the network and connected applications as needed. 

This is a state where all data is now liberated.

See what can happen when you set your data free on

Data Collaboration: change starts here

 A Data Collaboration Platform is the architectural model that evolves your data into a fully collaborative data network. Data Collaboration empowers connectivity and control by eliminating data fragmentation and data duplication and the need for costly and time-consuming integration.

With a Data Collaboration Platform, data is available to whoever needs it, accessed simply and freely wherever it's needed.

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Data's new DNA

Liberated data is based on a semantic model that does not have to map to any specific system or application. The result is a completely different kind of data. Data that can be extended beyond individual applications, easily interconnected with other data and managed through a self-serve data browser.


Data is liberated directly from existing applications (i.e. CRM) or is newly created independent of any application.


The data network can automatically notify data managers of anomalies and even repair errors.


Data free from application control is easier to protect and manage. Application restrictions no longer exist. 

 A liberated data model is an entirely independent data network free of application binding.


With liberated data, there's no need for integration efforts or copying databases to get multiple applications to work together.


Liberated data creates an environment where any user can access data directly, under defined access governance.


Users become data 'creators', with the ability to grant further federation and governance to others as needed.

In a Data Collaboration Platform, defined by a liberated data model, business intelligence and plasticity can now take place throughout the entire enterprise.

Intelligence is the new platform.

Dig deeper into data liberation

See Data Collaboration in action!

Connected data without the effort, time, and cost of traditional data integration.