What Is Data-Centric Architecture? Reasons to Adopt It

For most of human history, it was widely believed that the Earth was the center of everything. 

Nicolaus Copernicus published his definitive mathematical model of a heliocentric solar system in 1543. Galileo Galilei defended it in the early 1600s. Isaac Newton defended it in the late 1600s. But the Catholic Church didn’t officially accept the sun’s place in the center of the solar system until 1822. 

What does this have to do with your enterprise architecture system?

Everything. 

Because the way humanity viewed the Earth for all those years is the exact same way developers and architects view applications today – as the immutable center of everything. But the truth is that they’re wrong.

It is data – not applications – that belongs at the center of your enterprise architecture. And it is a data-centric approach that will unlock incredible advantages for your business today and in the future.

Why modern enterprises must embrace data-centricity

There’s a simple, although somewhat underwhelming, reason that modern enterprise architecture evolved to take an app-centric approach. It can be traced back to the first relational databases, which appeared in the 1970s, and the way they tied data to specific applications.

Big or small, every application has its own specific model for data, and developers have had to build around that model. And that was never really a problem… until it was a major problem.

The proliferation of app-centric enterprise architecture has created a world where new solutions require custom access controls, lengthy integration projects, and lots and lots of data replication. Every time you want to create a new solution or introduce a new capability, you’re forced to perform these ramp-up tasks of copying data and integrating systems.

As a result, enterprise architectures are brittle and fickle, and one of the big rules for enterprise IT teams is to avoid changes to the legacy systems at all costs, less they break something critical. This is no way for today’s advanced businesses to operate. 

And all this time, apps were really just a way to get to what really matters: the data. Your most complicated (and expensive) application would be nearly valueless without the names, numbers, and other data that it handles, right? Meanwhile, that same data would be just as important to your business regardless of what application you used to access it. 

Your dependence on a specific application doesn’t come from the application itself, so much as the numerous solutions and integrations you’ve built on top of that application, each one making it that much harder to switch platforms. But if you could use that new data with a different application instantly, without needing integration efforts, it would have just as much value in your new system as it does now.

Data-centricity puts data at the heart of your architecture, where it belongs.

Data-centricity solves persistent business problems

By putting data at the center of your enterprise architecture, you’ll unlock operational efficiencies that were impossible under the old, app-centric paradigm, and solve a number of problems that previously seemed un-solvable. Here are some of the key differences you’ll experience.

Data replication

Data replication is one of the biggest problems for modern enterprise IT teams to manage, and yet every it is a fundamental necessity of an app-centric architecture. All of those integration efforts, which are required for virtually every new project, involve standing up new databases and copying over old data. As a result, your IT team spends a large portion of its time functioning as a very expensive data copying machine. This is not an efficient use of their time or their capabilities.

On top of that, your data is only ever as secure as its most vulnerable copy, which makes such rampant data replication a clear liability. Modern enterprises can have hundreds or even thousands of copies of data, and losing control over even a single copy can be disastrous.

But because of the established paradigm of app-centric thinking, enterprises have accepted widespread data replication as a necessity, and its many shortcomings as just part of the cost of doing business.

This is a bit like all of the mental gymnastics that went into maintaining a geocentric view of the solar system, despite all of the observable evidence that things made much more sense if you accepted the sun as the center of things. 

Data-centricity signals the end of data replication, because data is no longer tied to the particular application that creates it. Instead, it offers a single source of truth and uses links instead of copies to share data across multiple applications. This allows you to “reuse” data without making copies, and frees up your IT team so they can focus on building solutions instead of copying data.

Data silos

When was the first time you heard about the importance of knocking down data silos? Ten years ago? Fifteen? Everyone knows data silos are bad, so why are they still everywhere?

It should be no surprise that data silos exist and persist because of app-centric design. As long as data is tied to the applications that create it, you’ll always need new databases when standing up new software. Because of this, “breaking down” data silos has really just meant “moving from smaller silos into bigger silos.”

While building a bigger silo provides a temporary solution, eventually you’ll find that you need to upsize again to “break down” the big silos you’ve been creating. The only way to actually stop building data silos is to move to a data-centric architecture.

Instead of standing up new databases and thus building bigger silos, data-centricity allows you to separate data from the application and move it into a network known as a data collaboration platform or data fabric. These platforms allow data to exist as a network, and this networked approach means that data can be shared and reused across various apps without making copies.

Because apps can reuse data in this network through links instead of copies, you’re never going to need a “bigger silo”. Any application you connect to your data collaboration platform will be able to make use of any data already on the platform. There’s simply no other way to create a permanent alternative to data silos.

Limited business agility

No matter how good your IT department is, or how advanced your technology may be, a business can only operate as fast as its tech stack allows. For app-centric businesses, any new project requires integration efforts and other groundwork before your existing data is ready to be applied to a new solution. This foundational work routinely eats up to 50% of an IT team’s time and budget for any given project.

The more complex the systems are, the more difficult they become to change. This is why legacy architecture is generally brittle and difficult, if not impossible, to change - change one piece and you threaten breaking the whole thing.

Low-code and “no-code” technology may enable faster delivery from a front-end perspective, but they do nothing to eliminate the root cause of your problems or actually make your enterprise more agile. At best, they simply provide an illusion of improved efficiency. But until you address the complexity that limits your flexibility in the first place, you’re not creating meaningful change.

Data-centricity introduces plasticity to enterprise schema, meaning the ability to change and adapt in real time. This is the meaningful change you need in order to permanently and immediately create enterprise agility. The effects of this are remarkable.

By eliminating data copies and integration efforts, new solutions can be built in days instead of weeks. It suddenly becomes possible to operationalize new technology on timelines that were only fantasy under an app-centric approach.

For example, business agility is essential for fighting financial fraud through AI. The more advanced the fraud-detection algorithms become, the more devious and creative the criminals become in order to evade the algorithms.

When both sides are using app-centric approaches, it is difficult for either to gain a significant advantage. But when one side uses data-centricity to suddenly reduce the time it takes to implement change, it makes it next to impossible for the other side to keep up.

The importance of operationalizing data-centricity 

A recent study by the Harvard Business Review, involving 1,500 companies, found that significant performance improvements happen when humans and machines work together. But achieving that sort of symbiosis isn’t easy with today’s app-centric technology. It becomes much easier through data-centricity and the data collaboration platform.

The key to this is the ease with which data-centricity allows humans and artificial intelligence (AI) to leverage each other’s complementary strengths. Humans excel at teamwork and cooperation, creativity, and social interactions, while machines offer unmatchable computational speed and scalability. Businesses require both skill sets, and benefit from situations that maximize the efficacy of each.

Data-centricity is an ideal solution for taking full advantage of collaboration between people and AI by streamlining access to data and allowing humans and systems to work together in harmony. It democratizes data, giving data owners unprecedented control and empowering new solutions and new business insights. It removes the barriers that make AI difficult to work with, paving the way for AI-powered solutions to revolutionize the way you do business.

How data-centricity improves compliance with new data privacy protections

One of the biggest benefits of data-centricity is the way it improves the lives of compliance officers, particularly in an era of increasing data regulations. As companies are forced to comply with things like the European Union’s General Data Protection Regulation (GDPR), it becomes even more important to have control over your enterprise data.

For example, the GDPR gives consumers the right to receive an explanation for any algorithm-based decision. This includes things like the rate offer on a credit card or mortgage. How much data does your enterprise use to make such decisions? And how difficult would it be for you to provide such data if it were requested?

California’s Consumer Privacy Act (CCPA) gives consumers “the right to be forgotten,” as in to require that a company delete all data associated with that user. Today’s climate of data copying can make such a request functionally impossible to fulfill, as companies simply have so many data copies that they don’t even know where all of them exist. 

Data compliance officers must ensure that they’re prepared for such regulations, and for the near-certainty of national data privacy reform at some point in the future. By eliminating data copies through a data-centric approach, it becomes far easier to meet these standards. 

Data-centricity is the way forward

Just like the sun has always been at the center of the solar system, data has always been at the center of your enterprise. It’s finally time to start treating it that way. Those who recognize this fact and are quick to embrace it will find themselves on the leading edge of a revolution, but they will find themselves there with company.

Some of the most complex organizations in the world, including highly-regulated financial institutions, have already started the transition to data-centricity. 

These businesses are accelerating their solution delivery, de-risking their data security, and unlocking real business agility. And every day, they’re increasing the advantages they have over companies who remain centered on applications.

If you’re still adhering to the 40-year-old app-centric approach, it will be next to impossible to compete with modern, data-centric businesses as their numbers continue to grow. After all, successful businesses already operate as efficiently as possible, and squeezing meaningful change out of your architecture is extremely difficult. 

Instead of eking out fractions of a percent in improvement, it’s time to embrace a paradigm change like data-centricity. When you can eliminate integration efforts and instantly free up 50% of your IT resources on any project, you will have the bandwidth you need to deliver enterprise-changing innovation.

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