How To

How To Ensure Data Centricity in the Enterprise

September 19, 2023 | min

Data flowing from a central point illustrates the concept of data centricity

Data is at the heart of everything that happens in IT, but it is also easy to lose sight of its true value in a landscape where data is growing ever more rampant and prolific. 

Organizations that follow a true data-centric approach to development and deployment can accomplish those tasks with greater focus and efficiency. That is why it is so necessary for leaders to find a simple solution that ensures data centricity even in complex environments.

Key Takeaways:

  • One way to ensure that a company follows a data-centric approach is by taking measures to avoid data overflow that often occurs in other data-driven strategies.
  • Transitioning away from legacy infrastructure facilitates data-centric methods by ensuring data is well-accommodated and not prone to loss.
  • Embracing cloud infrastructure is another way to ensure that an organization remains data-centric by allowing for users to access shared data models from any location.

Learning more about what it means to be data-centric and how decision-makers can ensure the success of data-centric processes will give enterprises new opportunities for success in the modern IT landscape.

What is data centricity?

Data-centricity recognizes the pivotal and versatile role of data within the broader enterprise and industry landscape, considering information as the foundation asset of enterprise architectures. A data-centric architecture is one in which data itself is the focus and is regarded as the primary and most valuable asset.

Data-centric processes operate on a common data model. All aspects of all applications in the data-centric environment utilize the shared model, therefore promoting consistency and efficiency.

An organization should build its data-centric architecture on a model that can help to streamline or quantify business strategies, as well as make accurate projections of a strategy’s possible outcomes.

In an architecture that is not data-centric, applications might be the central focus of all workloads. The downside to this approach is the possibility of investing time, effort, and resources into different data models for each application.

Ultimately, the core tenet behind data centricity is positioning data as an asset. This is in contrast to an application-centric approach, as applications inevitably change, undergo modification, or rotate out of use as replacements emerge from development.

Avoid data-driven pitfalls

Being data-driven is a mindset, meaning it is not necessarily synonymous with being data-centric. Data-centric refers to the architecture itself, rather than a business’s strategies, which may be data-driven.

In fact, being data-driven can actually make an enterprise less data-centric if it falls into the habit of aimlessly collecting too much data and trying to act upon too many scattered insights. The potential pitfall of being too data-driven is in relying on too many data models, while an effective data-centric solution entails utilizing only one shared model.

Another common and dangerous pitfall in the data-driven approach is a lack of data governance. This refers to the set of rules a company enforces on how they collect, store, use, and dispose of data. Without governance, there is data chaos, and employees and stake-holders will struggle to secure or access the data they need in crucial moments.

It is possible to add data centricity to a data-driven enterprise by implementing a core data-centric model and using that model as the driving force behind business decisions and finding meaning in analytics.

Transition from legacy infrastructure

Modern businesses must manage massive amounts of data, which can be a nearly impossible task on outdated legacy infrastructure. Outdated on-premises hardware lacks the flexibility that organizations need when prioritizing data-centric strategies. It is also often the case that legacy infrastructure is hard to merge effectively with other, more modern hardware devices in a typical data-centric architecture setting.

It can even be difficult to simply meet data storage needs on legacy hardware. There is also the risk of losing data if a legacy server dies or if there are compatibility issues when migrating to new infrastructure.

The solution is to transition away from legacy infrastructure toward more modern hyperconverged infrastructure (HCI) as soon as possible. HCI facilitates data-centric strategies by increasing data visibility and by allowing for data storage in a pooled, silo-less fashion.

Fortune Business Insights reports a global market size for hyperconverged infrastructure of USD 5.88 billion in 2020 and projects that market size to grow to USD 32.19 billion by 2028. It is possible to interpret this projected growth as an indication of industry-wide interest in the use of HCI for furthering data centricity and overall infrastructure flexibility.

Embrace cloud solutions

The cloud offers a flexible platform free from the constraints of legacy infrastructure, helping enterprises accelerate their journey to data centricity. Cloud processes are also relatively future-proof, guaranteeing that data loss will not occur as a result of incompatibility. 

Cloud solutions can help companies visualize and break down data in a comprehensible way. The ideal cloud platform is one that comes equipped with inherent data visualization and cloud visualization tools that operators can use in their data-centric strategies to ensure visibility and transparency every step of the way.

It is also important to consider that data-centric practices require that the user can access the core data model from any location regardless of where it resides. When that data model resides in the cloud, it is accessible from any device and can even move across clouds in a hybrid multicloud environment.

The Nutanix Cloud Platform (NCP) ensures that all data in the entire cloud ecosystem remains accessible by placing a layer of abstraction over all locations in the network. In this way, operators can interact with all clouds from a standardized interface.  

For eight reasons on how HCI can benefit your business-critical apps and databases, take a look at this Nutanix eBook.

The enterprise solution that ensures data centricity

Ensuring data centricity in the modern IT environment requires a company-wide mindset that focuses on shared data models and that is distinct from other, less focused data-driven approaches. It also requires a future-proof infrastructure that preserves data as the organization’s most valuable asset and allows for operators to always access that data on demand. 

Nutanix is the enterprise solution that accommodates these requirements while also guaranteeing simplicity for users and administrators. The Nutanix Cloud Infrastructure (NCI) emphasizes standardization based on secure hyperconvergence that empowers businesses to deliver applications with a data-centric approach at any scale. 

Keeping in mind that being data-centric entails following a single shared data model across all applications, it goes without saying that simplicity is a key attribute of data centricity. The ideal infrastructure for data-centric architecture, then, should be one that extends that simplicity rather than adding layers of unnecessary complexity. 

Learn more about simplifying data management as well as the key differences between converged and hyperconverged infrastructure (HCI).

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