Manufacturing companies are constantly trying to strike the right balance across their product innovation, engineering, and logistics functions. Since these highly interconnected processes span a complex web of technology partners (vendors) and distribution / channel partners, they end up creating gaps in data, lead to information latency, and expose new barriers that create complex associations across operations and constituents.
Organizations looking to standardize these processes and streamline how they collect, analyze, and manage growing volumes of data can benefit greatly by adopting data fabric.
By connecting the right data to the right people, data fabric optimizes access to distributed data – no matter where it is stored and in which format. Since the data fabric architecture is data source agnostic (cloud/server/edge), it allows manufacturers to better harness the power of hybrid cloud environments, standardize data storage, and radically simplify data management across complex data landscapes.
It provides a powerful architecture that standardizes data management practices and practicalities across cloud, on premises, and edge devices. A data fabric improves end-to-end performance, controls costs, and simplifies infrastructure configuration and management.
With reports estimating the data fabric market to grow from $1.2 billion in 2021 to $2.4 billion by 2028, at a CAGR of 10.3%, the promise that this new data management technique offers is beyond comparison.
Read on to learn how!
With the volume and variety of manufacturing data constantly growing, there is a pressing need for manufacturers to enable real-time analytics and for smarter decisions. But with the existence of several thousand data sources, and new ones constantly being added, these companies find themselves struggling to standardize data management practices across different devices and environments. This eventually impacts the visibility they have across their business as well as the accuracy and timeliness of the decisions they make.
Although traditional data management strategies worked in a time when the enterprise data landscape was fairly uniform, structured, and simple, in today’s highly complex and dynamic manufacturing environment, where new devices and data sources constantly emerge, shifting from a reactive to a responsive data strategy is vital for survival. Only such a strategy can allow manufacturers to effectively manage data across multiple endpoints spread across multiple hybrid and multi-cloud environments.
Gartner defines data fabric as, “a design concept that serves as an integrated layer (fabric) of data and connecting processes. It utilizes continuous analytics over existing, discoverable and inferenced metadata assets to support the design, deployment and utilization of integrated and reusable data across all environments, including hybrid and multi-cloud platforms”.
As a modern architecture that offers capabilities across multiple endpoints, a data fabric enables organizations to standardize data management spanning various environments. Offering a set of data services that establish data visibility and uncover timely business insights, data fabric allows manufacturing companies to have access to the data they need to monitor and control their business, protect their data, and ensure security across the enterprise. Such insight allows them to keep up with business demands and gain a competitive edge in the extremely crowded and competitive manufacturing landscape.
To establish a data fabric architecture that delivers unmatched business value, it is important for organizations to establish a robust technology base, identify required capabilities, and evaluate existing data management tools to unearth gaps and opportunities. They also need to implement mechanisms that allow the data fabric to identify, integrate, and analyze different kinds of metadata and represent it graphically for quick sharing and analysis of data.
The pace and volume of data that is being generated in the manufacturing industry are humongous, to say the least. Add to it the increasing number of smart devices and users that is causing a surge in the adoption of cloud and other hybrid-environment platforms. Although all these devices – and all the data they are generating – are helping companies improve manufacturing efficiency and throughput, security, and privacy concerns that these devices bring cannot be ignored.
At the same time, organizations are increasingly looking to bridge the gap between IT systems used for data analysis and OT systems used for monitoring events, processes, and devices, build integrated processes, and enable seamless information flow.
As manufacturing companies embark on the digital transformation journey, the adoption of data fabric can open doors to several benefits.
Here’s looking at the numerous ways in which manufacturers can leverage data fabric:
The COVID19 disruptions have brought global supply chains to the brink. As the struggle to balance supply and demand lingers, manufacturers have come to realize that poor data management strategies are a prime reason for their inability to manage complex supply chain networks and adapt them to change. As consumer demand continues to fluctuate, the adoption of data fabric can enhance enterprise visibility and control, boost production throughput, and allow manufacturers to keep pace with varying end-user requirements – all while reacting to the changing market environment with agility.
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