Are you asking the right questions about your data?

2 min read
January 23, 2023

As companies continue to navigate the rapidly evolving landscape of data management, a question on the minds of many is whether next-generation data architecture models such as data fabric, data mesh, and data graphs are now commonplace... or if organizations are still trying to figure out how to best design for these approaches, and is there something else out there that exists that has pulled the best bits of all of these together, into one unifying platform.

There’s a bit of nuance to this story as well because the models mentioned above are actually more accurately overlapping models of progression rather than single next-generation data architectures. While many of these approaches have been around for quite some time, there has been extensive innovation in recent years, with a wider range of these offerings now available. 

One emerging technology that does seem to be a best-of-breed around this modelling is a new category known as dataware, which introduces a fundamentally unique approach to modern data architecture. A dataware platform enables organizations to maintain their data in a network architecture that can power an unlimited number of digital solutions, making database silos and data integration obsolete. Dataware also incorporates elements of data fabric and other data products, making it a true "super category" in the world of data management software.

But what advantages does this unique architectural approach provide for businesses? Dataware's network-based architecture supports a new approach to digital innovation that effectively ends the point-to-point data integration which can often drain half of entire IT budgets. As a ‘zero-copy’ platform, dataware enables true collaboration on datasets from human, system, and machine-based sources of intelligence. Such collaborations are a key element of what is known as the data-centric approach to development in which data-level attributes (including owner-defined access controls) and active metadata serve to reduce the need for complex application code.

The net result is dramatically shorter build times, lower project costs, enhanced operational intelligence, and levels of data governance and data protection simply not possible with other more traditional data management technologies.

Perhaps the real question to ponder is what has taken so long for this approach to surface, Why is it that applications have been in control of data for so long, creating endless data silos that inhibit real-time collaboration and expedited solutions delivery?  Similarly, why are there still ever-increasing levels of copy-based data integrations being put in place, severely adding to compliance and security headaches? Data integration hubs and data warehouses are fundamentally just workarounds that mitigate the negative side effects of data fragmentation. They do nothing to address the underlying problem.

A Dataware platform seems to be the answer. 

For those looking to get started with or further develop these next-generation architectural approaches, industry experts recommend focusing on changing the delivery of new digital solutions, using dataware, to a project-by-project approach that steadily reduces an organization’s data silos, data integration, and complex code, and thereby avoids the shortcomings of ‘rip and replace’ approaches that fail to accommodate pre-existing digital solutions and IT investments.