Highlights:
- Data fabric is a collection of data services offering consistent capabilities across various endpoints in hybrid multi-cloud systems.
- In IT organizations with dynamic data workloads dispersed across globally distributed infrastructure systems, the data fabric design is especially helpful.
With organizations using a varied set of applications and given the dynamic nature of data, it’s becoming difficult for organizations to become data-driven and manage data.
Over the past two years, organizations have realized the importance of data flexibility for their business. Research shows that 92% of enterprises believe agility would enable better decision-making across their operations. At the core of flexible data lies agility, which enables trusted data to enhance efficiency and reach customers effectively. The fact is that to survive in today’s digital world organizations need to adjust to market shifts.
This blog looks closely at data fabric, its components, and the benefits it can offer organizations.
What is data fabric?
Data silos have become a constant problem today. Much of the data remains hidden across the hybrid mix of infrastructure environments. And with data processing cycles getting longer, organizations need vast data management capabilities to tide over the limitations facing complex multi-vendor, multi-cloud, and evolving data environments.
Data fabric is an emerging design concept that helps solve various data management challenges, including the high cost of data integration, rising demand for real-time data, and data maintenance. It is a collection of data services offering consistent capabilities across various endpoints in hybrid multi-cloud systems.
Its architecture is powerful enough to standardize data management methods and practicalities across cloud, on-premises, and edge devices. Data visibility and insights, data access and management, data protection, and security are the many benefits that a data fabric offers.
Data fabric uses both human and machine capabilities to access existing data or support consolidation. It continuously recognizes and links data from many applications to find distinctive, commercially significant relationships among the data points available.
With data fabric infrastructure, massive data silos and disconnected architecture are a thing of the past. The foundation of data fabric is a comprehensive set of data management tools that guarantee consistency between integrated environments. It streamlines development, testing, and deployment while safeguarding assets round-the-clock by automating laborious administration tasks.
Components of data fabric
Traditional data systems such as DataOps were focused solely on operationalizing the data lake, but data fabric delivers capabilities that unify diverse and distributed data assets.
To put it simply, frameworks such as DataOps are used by organizations to design, implement, and maintain a distributed data architecture. It helps them comprehend the data generated and stored in a highly distributed infrastructure environment. But data fabric, a unified data management platform architecture, can combine end-to-end data management processes as follows:
- Data processing: Curating and transforming data offers analytics-ready data for BI and AI.
- Data orchestration: Provides a thorough understanding of the data pipeline. It helps manage the data flow and coordinates it.
- Data ingestion: It utilizes data from a variety of sources, including databases, cloud-based programs, and data streams. Real-time and stream processing are made simpler by it.
- Data governance: It enables the handling of metadata locally in accordance with overall business standards and centralizes the complete data governance process.
The utility of data fabric in a multi-cloud environment
The data fabric design is especially helpful in IT organizations that involve dynamic data workloads dispersed across globally distributed infrastructure systems. Here are some benefits that the data fabric architecture offers in today’s cloud-based IT enterprise environment:
Running a hybrid cloud: Organizations invest in cloud infrastructure and storage solutions based on their needs for cost, security, availability, scalability, and services. Over time, these requirements have evolved, forcing them to either switch vendors or pursue other cloud models as workable substitutes.
In the latter case, cloud companies tend to lock consumers into their service, making data migration an expensive and difficult task for their clients.
Organizations can overcome many of the technical difficulties associated with managing a broad portfolio of infrastructure and data storage deployments by using data fabric. Based on shifting technical and business needs, customers can take advantage of the freedom to operate mission-critical data-driven IT services, apps, storage, and access from various hybrid IT infrastructure resources.
Seamless transition to the cloud: When processing a diverse portfolio of data stored in various places, data fabric helps organizations minimize disruptions caused by switching between cloud service providers and computational resources. As a result, data fabric significantly shortens the time to insights. Faster insights enable organizations to identify data patterns, understand trends and make proactive decisions. Businesses can, thus, cut competition while maximizing data investments by making better decisions through enhanced compute performance across all data channels.
High-performance data investments: Businesses put a lot of time and money into ensuring their apps and services deliver the best performance. This is particularly true for mission-critical applications that may need to process a rising amount of data as the user population increases or to handle erratic peak use demands.
Organizations must also invest in cloud storage solutions that provide appropriate performance levels to fulfil these demands. Similarly, the app or service may change and become a legacy solution for the future, and the usage requirement may also decrease. Regardless, the app should be able to give predictable performance whether the data is available at a highly accessible storage location or a low-cost economy storage infrastructure. Organizations can achieve this capability with data fabric and optimize their data investments based on evolving user requirements.
Futureproofing:  With data fabric, organizations enjoy the freedom to modify their infrastructure based on evolving technological requirements. Connecting diverse infrastructure endpoints to the integrated and consolidated data management framework becomes easier. Organizations need not worry about the data’s precise location.
Startup companies can take advantage of the flexibility that data fabric offers and select infrastructure environments that best suit the nature of their data. They can start by investing in low-cost cloud storage solutions until they gain traction and then invest in highly available storage capacity as per requirement. All infrastructure deployments will be compatible with the data management functionality, and enterprises may future-proof their data investments accordingly.
In Conclusion
Reports say that more companies now plan to make their data management program more flexible and agile in the near future. Corporations spanning industries are focusing more on data agility.
