A stable, reliable network is the backbone of today’s enterprise. On the flip side, an unreliable network or a network failure comes with severe consequences that have direct impact on the bottom line. Data fabric architecture has emerged as a tool to reduce friction, support data sharing across robust networking environments, and promote an environment that is more efficient and stable.
The data fabric market size was valued at $812.6 million in 2018, but is projected to reach $4,546.9 million by 2026, according to a report by Allied Market Research. This represents a growth of 23.8% from 2019 to 2026.
“With the rise in need for business agility and data accessibility,” Allied Market Research notes, “there is an increase in adoption of data fabric platforms as it enables applications and tools to access data using a wide range of interfaces that a business has deployed.”
What is Data Fabric?
Data fabric is a data management resource. It can be defined as a set of data services that provide consistent capabilities across a choice of endpoints. Data fabric reaches from on-premise environments to cloud-based landscapes with the objective to simplify, integrate, and accelerate. Data fabrics weave together cross-functional data connections. This connection creates efficiencies, operational fluidity, and network stability that can result in competitive advantages for the enterprise.
Here’s an example as it relates to a traditional supply chain data system. Without data fabric architecture in place, the supply chain operates much like a relay, handing off from one silo to the next down the line. When one part of the chain fails, the entire system can be brought to its knees. When a complex network of actors is in sync and able to adjust as needed, it ebbs and flows through the process without breakage or stoppage.
The Data Fabric Backstory
Today the mandate for enterprise IT is to deliver measurable business value with little exception. With the popularity of IoT, increase in the volume of unstructured data, growing presence of external data sources, and a trend toward hybrid multi-cloud environments, every data request has hoops to jump through. At the same time, data strategies, in this post-big data landscape, must be agile to succeed.
The competing problem is that enterprises are mired in data strategies that can’t pivot when an external factor requires them to do so. Structured data management systems excel in environments that are just that — structured. The problem is the world is growing less and less structured, and businesses need that fluid movement to remain competitive and viable. Enterprise data fabrics offer a better solution. By weaving together data from internal silos and external sources, data fabric creates a network of information to power business applications, data analytics, and artificial intelligence.
The Benefits and Challenges of Enterprise Data Fabrics
Like any solution, data fabrics offer a list of benefits and challenges for enterprise networks. Let’s examine a few of them.
The benefits of data fabrics:
- Adaptability – Data fabrics can answer questions that weren’t anticipated and morph to accommodate new requirements.
- Insight – Data is useless when it can’t be connected and assigned meaning. Data fabrics help you accomplish this task.
- Ease of Query – Data fabrics enable the business to query across all its data silos (both internal and external sources) and regardless of data structure.
- Seamlessness – Data fabrics enable you to modernize your existing systems. You won’t have to replace what you have to use this tool.
The challenges of data fabrics:
- Performance – Data fabrics must be capable of scaling both in and out, to support your requirements.
- Accessibility – Data fabrics have to support all your unique data sources to be a viable solution.
Data Fabric in an Enterprise Network Architecture
Data fabric becomes a key piece of the enterprise networking architecture by providing organizations with the means to better deal with overwhelming volumes of data as well as the ongoing evolution of business applications and network processing requirements. Data fabric becomes a connector of sorts that brings in data from all your sources, in all your unique structures. It uses your existing network tools and allows you to tap into data from one centralized, non-siloed place. In a world where agility is no longer optional and real data insights are the key to achieving goals, data fabric may be a necessity to get you there.
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