Most enterprise architectures are constructed on a basic false impression: that functions are the middle of all the things. Enterprise logic, techniques, and workflows revolve round them. Knowledge is pressured to evolve, combine, replicate, and migrate endlessly.
However what if that assumption is backwards?
It’s information — not functions — that belongs on the middle of your structure.
And reorienting round this reality unlocks a degree of agility, scalability, and innovation that app-centric pondering merely can’t ship.
This shift is already underway at main enterprises. By embracing data-centric structure, powered by fashionable information cloth software program, organizations are changing brittle app-bound techniques with resilient, interoperable, AI-ready ecosystems.
What’s data-centric structure?
An information-centric structure is a technique of structuring a system by placing information on the core of its design, performance, and decision-making processes. The structure prioritizes information as probably the most important and invaluable asset. Different system components are then constructed round it to make sure clean information administration, processing, and retrieval.
On this article, you’ll study why legacy application-first fashions are slowing your enterprise down and the way a data-centric method solves issues like information replication, siloed techniques, and integration overhead whereas unlocking true digital agility.
TL;DR: All the pieces you want to find out about data-centric structure
- What’s data-centric structure? A system design method that places information on the middle of your enterprise, enabling reuse, resilience, and agility at scale.
- How is it completely different from app-centric structure? App-centric techniques bind information to particular person apps. Knowledge-centric fashions decouple information and serve it to a number of apps by way of a shared cloth.
- Why is that this essential? It eliminates silos and redundancy, reduces integration prices, and allows sooner supply of recent options.
- What’s the enterprise influence? Higher velocity, decrease threat, higher compliance, and scalable foundations for AI and automation.
- How do you make the shift? Decouple information out of your apps, undertake an information cloth, and construct a shared information layer that connects all techniques from a single supply of reality.
Knowledge-centric structure vs. app-centric structure
Most enterprises as we speak nonetheless depend on an application-centric mannequin, the place information is created, saved, and managed inside particular person apps. This method made sense when apps have been less complicated and integrations have been uncommon. However as we speak, the explosion of instruments, customers, and use circumstances has revealed simply how rigid and dear app-centric pondering actually is.
In distinction, a data-centric structure reimagines the enterprise stack by putting information — not functions — on the core. As a substitute of duplicating information throughout techniques or forcing each new app to construct its personal database, a data-centric mannequin creates a single, reusable supply of reality that may energy any variety of functions.
Right here’s how the 2 approaches evaluate:
| Attribute | App-centric structure | Knowledge-centric structure |
| Major focus | Purposes and their inner information fashions | Enterprise information as a reusable, central asset |
| Knowledge possession | Tied to every utility | Owned independently and shared by way of hyperlinks |
| Integration efforts | Excessive (customized ETL, APIs, replication) | Low (reuse by way of unified information cloth) |
| Knowledge duplication | Frequent, typically uncontrolled | Eradicated or minimized by way of linking |
| Agility and scalability | Low, on account of brittle integrations | Excessive, because of composable, adaptable information |
| Compliance readiness | Laborious to hint or delete all information copies | Central management makes compliance extra manageable |
| Utility switching prices | Excessive; information and logic are tightly coupled | Low; apps are replaceable, information stays intact |
| Collaboration potential | Siloed groups and fragmented insights | Cross-functional entry and shared intelligence |
The distinction isn’t simply technical — it’s transformational. App-centric techniques deal with information as a byproduct of software program, making it onerous to reuse, govern, or evolve. In the meantime, a data-centric mannequin views information as the inspiration of the enterprise, enabling sooner innovation, stronger compliance, and AI readiness.
By shifting to a data-centric structure, enterprises break away from legacy complexity and begin treating information as a strategic asset, not a facet impact of utility use. This alteration unlocks the form of operational flexibility fashionable companies have to compete, scale, and evolve.
Why fashionable enterprises should embrace data-centricity
There’s a easy, though considerably underwhelming, purpose that fashionable enterprise structure developed to take an app-centric method. It may be traced again to the primary relational databases, which appeared within the Seventies, and the best way they tied information to particular functions.
Large or small, each utility has its personal particular information mannequin, and builders have needed to construct round that mannequin. And that was by no means actually an issue, till it turned a significant downside.
The proliferation of app-centric enterprise structure has created a world the place new options require customized entry controls, prolonged integration initiatives, and in depth information replication. Each time you wish to create a brand new answer or introduce a brand new functionality, you’re pressured to carry out these ramp-up duties of copying information and integrating techniques.
Because of this, enterprise architectures are brittle and fickle. One of many large guidelines for enterprise IT groups is to keep away from adjustments to legacy techniques in any respect prices, lest they break one thing crucial. That is no method for as we speak’s superior companies to function.
And all this time, apps have been actually only a solution to get to what actually issues: the information. Your most intricate (and costly) utility could be almost worthless with out the names, numbers, and different information that it handles, proper? In the meantime, that very same information could be simply as essential to your corporation no matter what utility you used to entry it.
Your dependence on a particular utility doesn’t come from the appliance itself, a lot because the quite a few options and integrations you’ve constructed on high of that utility, each making it that a lot tougher to modify platforms. However in the event you may use that new information with a special utility immediately, with no need integration efforts, it will have simply as a lot worth in your new system because it does now.
Knowledge-centricity places information on the coronary heart of your structure, the place it belongs.
How data-centricity solves persistent enterprise issues
By placing information on the middle of your enterprise structure, you’ll unlock operational efficiencies that have been unattainable below the previous, app-centric paradigm, and clear up various issues that beforehand appeared unsolvable. Listed here are among the key variations you’ll expertise.
Knowledge replication: the invisible drain on assets and safety
Knowledge replication is likely one of the greatest issues for contemporary enterprise IT groups to handle, and but each it’s a basic necessity of an app-centric structure. All of these integration efforts, that are required for just about each new undertaking, contain standing up new databases and copying over previous information. Because of this, your IT staff spends a big portion of its time functioning as a really costly information copying machine. This isn’t an environment friendly use of their time or their capabilities.
Moreover, your information is barely as safe as its most weak copy, which makes rampant information replication a transparent legal responsibility. Trendy enterprises can have a whole lot and even hundreds of copies of knowledge, and shedding management over even a single copy could be disastrous.
However due to the established paradigm of app-centric pondering, enterprises have accepted widespread information replication as a necessity, and its many shortcomings as simply a part of the price of doing enterprise.
It is a bit like all of the psychological gymnastics that went into sustaining a geocentric view of the photo voltaic system regardless of all of the observable proof that issues made far more sense in the event you accepted the solar as the middle of issues.
Knowledge-centricity alerts the top of knowledge replication, as a result of information is not tied to the actual utility that creates it. As a substitute, it provides a single supply of reality and makes use of hyperlinks as an alternative of copies to share information throughout a number of functions. This lets you “reuse” information with out making copies, and frees up your IT staff to allow them to concentrate on constructing options as an alternative of copying information.
Knowledge silos: the inevitable final result of app-centric design
When was the primary time you heard concerning the significance of flattening information silos? Ten years in the past? Fifteen? Everybody is aware of information silos are unhealthy, so why are they nonetheless all over the place?
It ought to be no shock that information silos exist and persist due to app-centric design. So long as information is tied to the functions that create it, you’ll all the time want new databases when standing up new software program. Due to this, “breaking down” information silos has actually simply meant “shifting from smaller silos into larger silos.”
Whereas constructing an even bigger silo supplies a brief answer, ultimately you’ll discover that you want to upsize once more to “break down” the large silos you’ve been creating. The one solution to really cease constructing information silos is to maneuver to a data-centric structure.
As a substitute of organising new databases and thus constructing larger silos, data-centricity lets you separate information from the appliance and transfer it right into a community often called an information collaboration platform or information cloth. These platforms enable information to exist as a community, and this networked method signifies that information could be shared and reused throughout numerous apps with out making copies.
As a result of apps can reuse information on this community by way of hyperlinks as an alternative of copies, you’re by no means going to want a “larger silo”. Any utility you connect with your information collaboration platform will be capable of make use of any information already on the platform. There’s merely no different solution to create a everlasting various to information silos.
Restricted agility: the hidden value of app-centric complexity
Irrespective of how good your IT division is or how superior your know-how could also be, a enterprise can solely function as quick as its tech stack permits. For app-centric companies, any new undertaking requires integration efforts and different groundwork earlier than your current information is able to be utilized to a brand new answer. This foundational work routinely eats as much as 50% of an IT staff’s time and funds for any given undertaking.
The extra advanced the techniques are, the harder they change into to vary. This is the reason legacy structure is mostly brittle and tough, if not unattainable, to vary – change one piece and also you threaten to interrupt the entire thing.
Low-code and “no-code” know-how might allow sooner supply from a front-end perspective, however they do nothing to remove the foundation explanation for your issues or really make your enterprise extra agile. At greatest, they merely present an phantasm of improved effectivity. However till you tackle the complexity that limits your flexibility within the first place, you’re not creating significant change.
Knowledge-centricity introduces plasticity to the enterprise schema, which means the flexibility to vary and adapt in actual time. That is the significant change you want to completely and instantly create enterprise agility, and the results are outstanding.
By eliminating information copies and integration efforts, new options could be in-built days as an alternative of weeks. It all of the sudden turns into doable to operationalize new know-how on timelines that have been solely fantasy below an app-centric method.
For instance, enterprise agility is crucial for combating monetary fraud by way of AI. The extra superior the fraud-detection algorithms change into, the extra devious and artistic the criminals change into in an effort to evade the algorithms.
When each side are utilizing app-centric approaches, it’s tough for both to realize a major benefit. However when one facet makes use of data-centricity to all of the sudden cut back the time it takes to implement change, it makes it subsequent to unattainable for the opposite facet to maintain up.
Constructing a data-centric stack? Add observability to the inspiration. Discover the greatest information observability software program to make sure your pipelines are reliable, traceable, and resilient.
Why operationalizing data-centricity is crucial
Adopting a data-centric mindset isn’t sufficient; it’s important to operationalize it throughout your stack to unlock its full potential. Meaning constructing the infrastructure, processes, and tradition wanted to deal with information as a shared, strategic asset, not an afterthought of utility design.
This shift turns into particularly highly effective relating to two urgent enterprise priorities: AI integration and regulatory compliance.
Enabling human AI collaboration by way of shared information
In an app-centric mannequin, information is fragmented throughout functions, making it tough for AI techniques to entry constant, high-quality inputs. Meaning extra time wrangling information and fewer time producing perception.
Knowledge-centricity adjustments the equation. With a unified, linkable information basis:
- People contribute context, creativity, and decision-making.
- Machines apply velocity, sample recognition, and scale.
- Each use the identical information, in actual time, with out replication or rework.
This alignment turns AI from a siloed experiment into an embedded enterprise functionality and opens the door to extra adaptive, clever techniques throughout your group.
Simplifying compliance in an period of rising regulation
Knowledge-centricity additionally solves one of many hardest challenges in fashionable enterprise operations: compliance with evolving information privateness legal guidelines like GDPR, CCPA, and different world laws.
Beneath GDPR, customers have the correct to know how algorithmic choices —similar to mortgage approvals — are made. Beneath CCPA, they’ll demand that every one private information be deleted. In an app-centric world riddled with information copies, each requests could be almost unattainable to satisfy.
However with a data-centric structure:
- Knowledge isn’t duplicated throughout each app; it’s linked and managed centrally.
- Auditing, tracing, and deleting information change into much more easy.
- You may reveal compliance with out spending months on cleanup.
This isn’t nearly threat discount. It’s about regaining management over your information and being prepared for no matter new laws might come subsequent.
Challenges of adopting a data-centric structure
No enterprise transformation is freed from friction and data-centricity isn’t any exception. Whereas the advantages are huge, the trail isn’t all the time clean. Acknowledging the real-world challenges of adopting a data-centric structure is crucial to overcoming them and constructing the interior assist you’ll want for fulfillment.
Listed here are 4 of the most typical obstacles you’ll encounter on the journey, together with methods to beat them:
Legacy system lock-in
Many enterprises nonetheless depend on core techniques which can be a long time previous—and deeply entrenched in app-centric logic. These techniques typically resist change as a result of they’re brittle, undocumented, or mission-critical.
You don’t want to tear and substitute legacy techniques to change into data-centric. Begin by wrapping them with an information entry layer or information cloth that enables exterior apps to work together with the information with out disturbing the legacy logic. This method allows incremental change, reduces threat, and allows you to step by step shift to data-centricity with out shutting down operations.
Cultural resistance
Shifting from app possession to shared information stewardship is extra of a cultural change than a technical one. Groups could also be hesitant to surrender management or change acquainted workflows.
Create a cross-functional information council to determine governance, talk wins from pilot initiatives, and contain key stakeholders early. Place data-centricity not as a lack of management however as a solution to allow innovation, cut back redundant work, and make groups simpler.
Expertise gaps in information engineering or governance
Conventional enterprise IT groups might lack expertise with information modeling, semantic layers, or zero-copy entry patterns.
Spend money on coaching round fashionable information structure ideas, usher in specialised companions for early initiatives, and construct a middle of excellence (CoE) for information practices. Beginning with a smaller pilot staff might help develop inner experience with out overwhelming your group.
Knowledge high quality and observability points
Shifting towards a shared information mannequin magnifies the results of unhealthy information. If the information isn’t clear, well-defined, and reliable, reusing it throughout apps can multiply threat reasonably than cut back it.
Make information observability a first-class citizen in your structure. Implement monitoring instruments to trace pipeline well being, detect anomalies, and implement information SLAs. Excessive-trust information is the inspiration of a useful data-centric system.
Making the leap to a data-centric structure isn’t about avoiding challenges, it’s about selecting which issues you wish to clear up as soon as and for all. Whereas the trail requires change, it results in an setting the place your information is lastly free to assist each app, staff, and innovation you introduce.
transition from app-centric to data-centric structure
Making the shift to data-centricity isn’t only a know-how improve; it’s a mindset shift. Listed here are the important steps to information your enterprise by way of the transition:
- Stock and classify your information: Determine the place your information lives, who owns it, the way it’s accessed, and what its enterprise worth is. Begin creating an information map throughout your current techniques.
- Decouple information from functions: Separate the logic and possession of your information from the apps that create or use it. Set up the idea of shared, reusable information entities.
- Implement an information cloth or information collaboration platform: Deploy infrastructure that enables information to be accessed by way of hyperlinks, not copies, throughout your techniques, similar to an information cloth, information mesh, or decentralized information platform.
- Set up information governance frameworks: Create insurance policies for possession, entry management, versioning, and compliance. Make governance a core operate, not an afterthought.
- Shift integration pondering from “pipes” to “hyperlinks”: Cease constructing customized integrations for each new app. As a substitute, enable apps to hyperlink into current information, lowering the necessity for replication or ETL processes.
- Begin with a high-impact pilot: Select a use case with seen ROI (like analytics or compliance) to reveal the worth of data-centricity. Use it as a proof level for broader buy-in.
- Practice groups and evolve your tradition: Equip stakeholders with information literacy and replace processes to prioritize shared information possession and reusability over app-specific management.
- Scale incrementally: Develop the data-centric mannequin throughout enterprise models and functions in phases. Monitor outcomes to show worth and refine structure.
Knowledge-centric structure: Regularly requested questions
Q. What’s an information cloth?
An information cloth is a digital layer that connects and manages information throughout techniques with out replication. It allows real-time entry and sharing by way of hyperlinks as an alternative of copies, supporting data-centric fashions.
Q. How does a data-centric mannequin enhance information safety?
Fewer information copies imply fewer threat factors. Centralized information management by way of an information cloth or related platform makes it simpler to audit, safe, and delete delicate info when required.
Q. Can I implement data-centric structure with out changing legacy techniques?
Sure. You may “wrap” legacy techniques with an information entry layer or cloth, permitting them to take part in a shared information setting with no need to be replatformed or rewritten.
Q. What position does information observability play in a data-centric method?
An enormous one. Since information is shared throughout a number of techniques, monitoring high quality, lineage, and efficiency turns into important. Instruments for information observability assist keep belief and stop unhealthy information from spreading. See the top-rated information observability instruments on G2
Q. Is data-centric structure the identical as an information mesh?
Not precisely. Knowledge-centricity is the philosophy of placing information first. An information mesh is one solution to implement that philosophy — it treats information domains as merchandise and decentralizes information possession. Knowledge-centricity could be achieved by way of information mesh, information cloth, or a hybrid of each.
Knowledge-centricity is the best way ahead
Identical to the solar has all the time been on the middle of the photo voltaic system, information has all the time been on the middle of your enterprise. It’s lastly time to start out treating it that method. Those that acknowledge this truth and are fast to embrace it should discover themselves on the vanguard of a revolution, however they’ll discover themselves there with firm.
A number of the most advanced organizations on the earth, together with highly-regulated monetary establishments, have already began the transition to data-centricity.
These companies are accelerating their answer supply, de-risking their information safety, and unlocking actual enterprise agility. And on daily basis, they’re rising the benefits they’ve over corporations who stay centered on functions.
When you’re nonetheless adhering to the 40-year-old app-centric method, will probably be subsequent to unattainable to compete with fashionable, data-centric companies as their numbers proceed to develop. In spite of everything, profitable companies already function as effectively as doable, and squeezing significant change out of your structure is extraordinarily tough.
As a substitute of eking out fractions of a % in enchancment, it’s time to embrace a paradigm change like data-centricity. When you possibly can remove integration efforts and immediately unlock 50% of your IT assets on any undertaking, you should have the bandwidth you want to ship enterprise-changing innovation.
You may’t construct a data-centric structure with corrupt information. Monitor and safe your corporation information with the most effective data-centric safety software program.
This text was initially revealed in 2023. It has been up to date with new info.
